sklearn

'random' | 'nndsvd' | 'nndsvda' | 'nndsvdar' | 'custom' 'random' | 'nndsvd' | 'nndsvda' | 'nndsvdar' | 'custom'

None | 'random' | 'nndsvd' | 'nndsvda' | 'nndsvdar' None | 'random' | 'nndsvd' | 'nndsvda' | 'nndsvdar'

None | 'random' | 'nndsvd' | 'nndsvda' | 'nndsvdar' | 'custom' None | 'random' | 'nndsvd' | 'nndsvda' | 'nndsvdar' | 'custom'

array, [n_samples] array, [n_samples]

array, shape (n_samples,), optional array, shape (n_samples,), optional

array-like or sparse matrix array-like or sparse matrix

int, int,

"all" or array of indices or mask "all" or array of indices or mask

"array-like, shape (n_samples,) "array-like, shape (n_samples,)

"auto", "full" or "elkan", default="auto" "auto", "full" or "elkan", default="auto"

"linear" | "poly" | "rbf" | "sigmoid" | "cosine" | "precomputed" "linear" | "poly" | "rbf" | "sigmoid" | "cosine" | "precomputed"

'F', 'C' or None (default=None) 'F', 'C' or None (default=None)

'auto' (default), 'QR', 'LU', 'none' 'auto' (default), 'QR', 'LU', 'none'

'auto' or a list of lists/arrays of values. 'auto' or a list of lists/arrays of values.

'auto', int or array of ints 'auto', int or array of ints

'batch' | 'online', default='online' 'batch' | 'online', default='online'

'bic' | 'aic' 'bic' | 'aic'

'both' | 'components' | 'transformation' | None 'both' | 'components' | 'transformation' | None

'cd' | 'mu' 'cd' | 'mu'

'dense' (default) | 'sparse' | False 'dense' (default) | 'sparse' | False

'error' (default) or 'ignore' 'error' (default) or 'ignore'

'euclidean' | 'precomputed', optional, default: 'euclidean' 'euclidean' | 'precomputed', optional, default: 'euclidean'

'l1', 'l2' or None, optional 'l1', 'l2' or None, optional

'l1', 'l2', or 'max', optional ('l2' by default) 'l1', 'l2', or 'max', optional ('l2' by default)

'log' | 'squared' | 'multinomial' 'log' | 'squared' | 'multinomial'

'ovo', 'ovr', default='ovr' 'ovo', 'ovr', default='ovr'

'raise' (default) or numeric 'raise' (default) or numeric

'sigmoid' or 'isotonic' 'sigmoid' or 'isotonic'

'sigmoid' | 'isotonic' 'sigmoid' | 'isotonic'

'train' or 'test', 'all', optional 'train' or 'test', 'all', optional

(ignored) (ignored)

(int, int) (int, int)

(low, high), default=(0.05, 0.95) (low, high), default=(0.05, 0.95)

(m,) ndarray (m,) ndarray

(n_components, n_components) array, optional (n_components, n_components) array, optional

(n_samples, n_features) (n_samples, n_features)

(rows, columns) (rows, columns)

(sparse) array-like, shape (n_samples, n_features) (sparse) array-like, shape (n_samples, n_features)

(sparse) array-like, shape (n_samples, n_outputs) (sparse) array-like, shape (n_samples, n_outputs)

(sparse) array-like, shape = [n_samples, ], [n_samples, n_classes] (sparse) array-like, shape = [n_samples, ], [n_samples, n_classes]

(sparse) array-like, shape = [n_samples, ], [n_samples, n_classes]. (sparse) array-like, shape = [n_samples, ], [n_samples, n_classes].

(sparse) array-like, shape = [n_samples, n_classes] (sparse) array-like, shape = [n_samples, n_classes]

(sparse) array-like, shape = [n_samples, n_features] (sparse) array-like, shape = [n_samples, n_features]

0 < double < 1 (default=.8) 0 < double < 1 (default=.8)

0 or 1, optional (1 by default) 0 or 1, optional (1 by default)

1D array, shape (n_nodes, ) or None 1D array, shape (n_nodes, ) or None

1D array, shape (n_nodes-1, ) 1D array, shape (n_nodes-1, )

1d array-like 1d array-like

1d array-like, or label indicator array / sparse matrix 1d array-like, or label indicator array / sparse matrix

1d boolean nd-array 1d boolean nd-array

2-tuple, optional 2-tuple, optional

2D array 2D array

2D array (n_features, n_features), optional 2D array (n_features, n_features), optional

2D array of indices 2D array of indices

2D array, (n_features, n_features) 2D array, (n_features, n_features)

2D array, shape (n_components, n_features) 2D array, shape (n_components, n_features)

2D array, shape (n_nodes-1, 2) 2D array, shape (n_nodes-1, 2)

2D array, shape (n_test_samples, n_features), optional 2D array, shape (n_test_samples, n_features), optional

2D matrix 2D matrix

2D ndarray (n_features, n_features) 2D ndarray (n_features, n_features)

2D ndarray, shape (n_features, n_features) 2D ndarray, shape (n_features, n_features)

2D ndarray, shape (n_samples, n_features) 2D ndarray, shape (n_samples, n_features)

2D numpy.ndarray (n_alphas, n_folds) 2D numpy.ndarray (n_alphas, n_folds)

A collection of strings or None, optional (default=None) A collection of strings or None, optional (default=None)

A single callable or dict mapping scorer name to the callable A single callable or dict mapping scorer name to the callable

All parameters are stored in the Gaussian Process model object. All parameters are stored in the Gaussian Process model object.

BaseEstimator BaseEstimator

BaseEstimator, None, optional (default=None) BaseEstimator, None, optional (default=None)

BaseGradientBoosting BaseGradientBoosting

Batch object Batch object

BernoulliRBM BernoulliRBM

Boolean Boolean

Bunch Bunch

Bunch object Bunch object

Bunch object, a dictionary with attribute access Bunch object, a dictionary with attribute access

CSC or CSR matrix with shape (n_samples, n_features) CSC or CSR matrix with shape (n_samples, n_features)

CSC sparse matrix, shape (n_samples, n_features) CSC sparse matrix, shape (n_samples, n_features)

CSR matrix with shape (n_samples, n_features) CSR matrix with shape (n_samples, n_features)

CSR matrix with shape [n_components, n_features] CSR matrix with shape [n_components, n_features]

CSR or CSC sparse matrix, shape (n_samples, n_features) CSR or CSC sparse matrix, shape (n_samples, n_features)

CSR or CSC sparse matrix, shape=(n_samples, n_features) CSR or CSC sparse matrix, shape=(n_samples, n_features)

CSR sparse matrix, shape (n_samples, n_features) CSR sparse matrix, shape (n_samples, n_features)

CSR sparse matrix, shape = (n_samples, n_labels) CSR sparse matrix, shape = (n_samples, n_labels)

FeatureHasher FeatureHasher

FeatureUnion FeatureUnion

Ignored Ignored

Imputer Imputer

Kernel object Kernel object

LabelBinarizer object LabelBinarizer object

List of 2D ndarray, shape (n_features, n_features) List of 2D ndarray, shape (n_features, n_features)

List of float List of float

LossFunction LossFunction

Mapping Mapping

Mapping or iterable over Mappings Mapping or iterable over Mappings

Mapping or iterable over Mappings, length = n_samples Mapping or iterable over Mappings, length = n_samples

Mapping or iterable, optional Mapping or iterable, optional

Matplotlib axis object, default None Matplotlib axis object, default None

NearestNeighbors object NearestNeighbors object

None of an (n_components, n_components) ndarray None of an (n_components, n_components) ndarray

None or array, shape=(n_samples, n_components) None or array, shape=(n_samples, n_components)

None or collection of string or unicode None or collection of string or unicode

None or dtype, optional None or dtype, optional

None or float, optional. None or float, optional.

None | array, shape=(n_components, n_components) None | array, shape=(n_components, n_components)

None | array, shape=(n_features,) None | array, shape=(n_features,)

None | int | instance of RandomState None | int | instance of RandomState

None | list None | list

None, 'SA', 'SF', 'http', 'smtp' None, 'SA', 'SF', 'http', 'smtp'

None, 'l2' or 'l1' or 'elasticnet' None, 'l2' or 'l1' or 'elasticnet'

None, 0 or 1 None, 0 or 1

None, int or RandomState, default=None None, int or RandomState, default=None

None, str or object with the joblib.Memory interface None, str or object with the joblib.Memory interface

None, str or object with the joblib.Memory interface, optional None, str or object with the joblib.Memory interface, optional

None, str or object with the joblib.Memory interface, optional (default=None) None, str or object with the joblib.Memory interface, optional (default=None)

Numpy Array Numpy Array

Passthrough for Pipeline compatibility. Passthrough for Pipeline compatibility.

Pipeline Pipeline

RandomState RandomState

RandomState instance or None RandomState instance or None

Returns self. Returns self.

String. Name of csv file to be loaded from String. Name of csv file to be loaded from

TfidfVectorizer TfidfVectorizer

Tree object Tree object

True | False | 'auto' True | False | 'auto'

True | False | 'auto' | array-like True | False | 'auto' | array-like

True | False | array-like True | False | array-like

True | False | array-like, default=False True | False | array-like, default=False

True, False or 'auto' (default) True, False or 'auto' (default)

True, bool, True, bool,

['auto'|'arpack'|'dense'] ['auto'|'arpack'|'dense']

_CFNode _CFNode

a cross-validation generator instance. a cross-validation generator instance.

a cross-validator instance. a cross-validator instance.

a numpy dtype or None a numpy dtype or None

an estimator an estimator

an integer, (default 500) an integer, (default 500)

any any

array array

array (opt.), shape (n_samples_X, n_samples_X, n_dims) array (opt.), shape (n_samples_X, n_samples_X, n_dims)

array [n_core_samples] array [n_core_samples]

array [n_samples] array [n_samples]

array [n_samples_a, n_samples_a] if metric == "precomputed", or, [n_samples_a, n_features] otherwise array [n_samples_a, n_samples_a] if metric == "precomputed", or, [n_samples_a, n_features] otherwise

array [n_samples_a, n_samples_a] or [n_samples_a, n_samples_b] array [n_samples_a, n_samples_a] or [n_samples_a, n_samples_b]

array [n_samples_b, n_features] array [n_samples_b, n_features]

array [n_samples_b, n_features], optional array [n_samples_b, n_features], optional

array like or sparse matrix of size (n_samples, n_outputs) array like or sparse matrix of size (n_samples, n_outputs)

array like, matrix, sparse matrix array like, matrix, sparse matrix

array of float array of float

array of float, shape (n_features,) array of float, shape (n_features,)

array of float, shape = [n_samples] or [n_samples, n_outputs] array of float, shape = [n_samples] or [n_samples, n_outputs]

array of float, shape=(len(list(cv)),) array of float, shape=(len(list(cv)),)

array of floats array of floats

array of floats with shape [n_features] array of floats with shape [n_features]

array of int array of int

array of int or None, default=None array of int or None, default=None

array of int, shape = [n_samples] or [n_samples, n_outputs] array of int, shape = [n_samples] or [n_samples, n_outputs]

array of integers, shape: n_samples array of integers, shape: n_samples

array of labels array of labels

array of shape (n) array of shape (n)

array of shape (n_clusters, X.shape[0],) array of shape (n_clusters, X.shape[0],)

array of shape (n_clusters, X.shape[1],) array of shape (n_clusters, X.shape[1],)

array of shape (n_components, n_features) array of shape (n_components, n_features)

array of shape (n_components, n_features), array of shape (n_components, n_features),

array of shape (n_components, n_samples) array of shape (n_components, n_samples)

array of shape (n_features, n_components) array of shape (n_features, n_components)

array of shape (n_features, n_samples) array of shape (n_features, n_samples)

array of shape (n_features,) array of shape (n_features,)

array of shape (n_samples, n_components) array of shape (n_samples, n_components)

array of shape (n_samples, n_components), array of shape (n_samples, n_components),

array of shape (n_samples, n_dimensions) array of shape (n_samples, n_dimensions)

array of shape (n_samples, n_features) array of shape (n_samples, n_features)

array of shape (n_samples,) array of shape (n_samples,)

array of shape (n_samples_1, n_features) array of shape (n_samples_1, n_features)

array of shape (n_samples_2, n_features) array of shape (n_samples_2, n_features)

array of shape (n_samples_X, n_features) array of shape (n_samples_X, n_features)

array of shape (n_samples_X, n_samples_Y) array of shape (n_samples_X, n_samples_Y)

array of shape (n_samples_Y, n_features) array of shape (n_samples_Y, n_features)

array of shape = [n_classes] array of shape = [n_classes]

array of shape = [n_classes] or a list of such arrays array of shape = [n_classes] or a list of such arrays

array of shape = [n_features] array of shape = [n_features]

array of shape = [n_samples, n_classes] array of shape = [n_samples, n_classes]

array of shape = [n_samples, n_classes], or a list of n_outputs array of shape = [n_samples, n_classes], or a list of n_outputs

array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1. array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1.

array of shape = [n_samples] array of shape = [n_samples]

array of shape = [n_samples] or [n_samples, n_outputs] array of shape = [n_samples] or [n_samples, n_outputs]

array of shape [n_class] array of shape [n_class]

array of shape [n_components, n_samples] array of shape [n_components, n_samples]

array of shape [n_dim, n_dim] array of shape [n_dim, n_dim]

array of shape [n_features, n_components] array of shape [n_features, n_components]

array of shape [n_features, n_samples] array of shape [n_features, n_samples]

array of shape [n_features] array of shape [n_features]

array of shape [n_features] or [n_features, n_targets], optional array of shape [n_features] or [n_features, n_targets], optional

array of shape [n_features], optional (default=None) array of shape [n_features], optional (default=None)

array of shape [n_samples, 10] array of shape [n_samples, 10]

array of shape [n_samples, 2] array of shape [n_samples, 2]

array of shape [n_samples, 3] array of shape [n_samples, 3]

array of shape [n_samples, 4] array of shape [n_samples, 4]

array of shape [n_samples, n_features] array of shape [n_samples, n_features]

array of shape [n_samples, n_original_features] array of shape [n_samples, n_original_features]

array of shape [n_samples, n_selected_features] array of shape [n_samples, n_selected_features]

array of shape [n_samples,] or [n_samples, n_classes] array of shape [n_samples,] or [n_samples, n_classes]

array of shape [n_samples] array of shape [n_samples]

array of shape [n_samples] or [n_samples, n_outputs] array of shape [n_samples] or [n_samples, n_outputs]

array of shape [n_samples] or [n_samples, n_targets] array of shape [n_samples] or [n_samples, n_targets]

array of shape [n_subsets_of_features] array of shape [n_subsets_of_features]

array of shape shape array of shape shape

array of shape(n_samples) array of shape(n_samples)

array of shape(n_samples). array of shape(n_samples).

array of shape(n_samples, n_dimensions) array of shape(n_samples, n_dimensions)

array of size (n_estimators + 1, ) array of size (n_estimators + 1, )

array or CSR matrix of shape [n_samples, n_classes] array or CSR matrix of shape [n_samples, n_classes]

array or CSR matrix with shape [n_components, n_features] array or CSR matrix with shape [n_components, n_features]

array or CSR matrix, shape (n_samples, n_classes) array or CSR matrix, shape (n_samples, n_classes)

array or None, shape (n_targets,) array or None, shape (n_targets,)

array or indicator matrix array or indicator matrix

array or list of array of shape (n_classes,) array or list of array of shape (n_classes,)

array or list of array of shape = [n_classes] array or list of array of shape = [n_classes]

array or sparse (CSR) matrix of shape (n_samples, n_features), or array of shape (n_samples, n_samples) array or sparse (CSR) matrix of shape (n_samples, n_features), or array of shape (n_samples, n_samples)

array or sparse (CSR) matrix of shape (n_samples, n_features), or array of shape (n_samples, n_samples) array or sparse (CSR) matrix of shape (n_samples, n_features), or array of shape (n_samples, n_samples)

array or sparse CSR matrix of shape [n_samples, n_classes] array or sparse CSR matrix of shape [n_samples, n_classes]

array or sparse matrix array or sparse matrix

array or sparse matrix of shape (n_samples, n_classes) array or sparse matrix of shape (n_samples, n_classes)

array or sparse matrix of shape [n_samples,] or [n_samples, n_classes] array or sparse matrix of shape [n_samples,] or [n_samples, n_classes]

array or sparse matrix, shape = [n_samples, n_labels] array or sparse matrix, shape = [n_samples, n_labels]

array or sparse matrix, shape=(n_samples, n_features_new) array or sparse matrix, shape=(n_samples, n_features_new)

array with shape (n_samples * (n_samples - 1) / 2, n_features) array with shape (n_samples * (n_samples - 1) / 2, n_features)

array, array,

array, (n_components, n_features) array, (n_components, n_features)

array, (n_components,) array, (n_components,)

array, (n_samples, n_components) array, (n_samples, n_components)

array, (n_samples, n_features) array, (n_samples, n_features)

array, [n_clusters, n_features] array, [n_clusters, n_features]

array, [n_components, n_features] array, [n_components, n_features]

array, [n_samples, n_components] array, [n_samples, n_components]

array, [n_samples, n_features] array, [n_samples, n_features]

array, [n_samples] array, [n_samples]

array, [p, n_components] array, [p, n_components]

array, [p, q] array, [p, q]

array, [q, n_components] array, [q, n_components]

array, dtype float, shape (n_samples), optional array, dtype float, shape (n_samples), optional

array, optional, default None array, optional, default None

array, optional, shape (n_classes,) array, optional, shape (n_classes,)

array, optional, shape = [n_classes] array, optional, shape = [n_classes]

array, same shape as n_samples_leaf array, same shape as n_samples_leaf

array, shap (n_samples,) array, shap (n_samples,)

array, shape (1, n_features) if n_classes == 2 else (n_classes, n_features) array, shape (1, n_features) if n_classes == 2 else (n_classes, n_features)

array, shape (1, n_features) or (n_classes, n_features) array, shape (1, n_features) or (n_classes, n_features)

array, shape (1,) array, shape (1,)

array, shape (1,) if n_classes == 2 else (n_classes,) array, shape (1,) if n_classes == 2 else (n_classes,)

array, shape (1,) or (n_classes,) array, shape (1,) or (n_classes,)

array, shape (M, N) array, shape (M, N)

array, shape (M, N) or (M, ) array, shape (M, N) or (M, )

array, shape (n_components, n_features) array, shape (n_components, n_features)

array, shape (n_components,) array, shape (n_components,)

array, shape (k, n_features) array, shape (k, n_features)

array, shape (k,) array, shape (k,)

array, shape (n_alphas + 1,) | list of n_targets such arrays array, shape (n_alphas + 1,) | list of n_targets such arrays

array, shape (n_alphas, n_folds) array, shape (n_alphas, n_folds)

array, shape (n_alphas, n_folds) or (n_l1_ratio, n_alphas, n_folds) array, shape (n_alphas, n_folds) or (n_l1_ratio, n_alphas, n_folds)

array, shape (n_alphas,) array, shape (n_alphas,)

array, shape (n_bins,) array, shape (n_bins,)

array, shape (n_classes * n_features,) or array, shape (n_classes * n_features,) or

array, shape (n_classes) array, shape (n_classes)

array, shape (n_classes, ) array, shape (n_classes, )

array, shape (n_classes, n_features) array, shape (n_classes, n_features)

array, shape (n_classes, n_folds, n_cs) or (1, n_folds, n_cs) array, shape (n_classes, n_folds, n_cs) or (1, n_folds, n_cs)

array, shape (n_classes,) array, shape (n_classes,)

array, shape (n_classes,) or (1, ) array, shape (n_classes,) or (1, )

array, shape (n_classes,) or (n_classes - 1,) array, shape (n_classes,) or (n_classes - 1,)

array, shape (n_clusters, n_features) array, shape (n_clusters, n_features)

array, shape (n_clusters,) array, shape (n_clusters,)

array, shape (n_components) array, shape (n_components)

array, shape (n_components, n_components) array, shape (n_components, n_components)

array, shape (n_components, n_features) array, shape (n_components, n_features)

array, shape (n_components, n_features) | None. array, shape (n_components, n_features) | None.

array, shape (n_components, n_features, n_features) array, shape (n_components, n_features, n_features)

array, shape (n_components,) array, shape (n_components,)

array, shape (n_cs,) array, shape (n_cs,)

array, shape (n_cv_alphas,) array, shape (n_cv_alphas,)

array, shape (n_dims,) array, shape (n_dims,)

array, shape (n_estimators, n_samples) array, shape (n_estimators, n_samples)

array, shape (n_features) array, shape (n_features)

array, shape (n_features, ) array, shape (n_features, )

array, shape (n_features, ) or (n_targets, n_features) array, shape (n_features, ) or (n_targets, n_features)

array, shape (n_features, ) | None array, shape (n_features, ) | None

array, shape (n_features, n_alphas + 1) | list of n_targets such arrays array, shape (n_features, n_alphas + 1) | list of n_targets such arrays

array, shape (n_features, n_alphas + 1) or list array, shape (n_features, n_alphas + 1) or list

array, shape (n_features, n_alphas) array, shape (n_features, n_alphas)

array, shape (n_features, n_alphas) or (n_outputs, n_features, n_alphas) array, shape (n_features, n_alphas) or (n_outputs, n_features, n_alphas)

array, shape (n_features, n_components) array, shape (n_features, n_components)

array, shape (n_features, n_features) array, shape (n_features, n_features)

array, shape (n_features, n_nonzero_coefs) array, shape (n_features, n_nonzero_coefs)

array, shape (n_features,) array, shape (n_features,)

array, shape (n_features,) or (n_classes, n_features) array, shape (n_features,) or (n_classes, n_features)

array, shape (n_features,) or (n_features, n_targets) array, shape (n_features,) or (n_features, n_targets)

array, shape (n_features,) or (n_targets, n_features) array, shape (n_features,) or (n_targets, n_features)

array, shape (n_features,) | (n_targets, n_features) array, shape (n_features,) | (n_targets, n_features)

array, shape (n_folds, n_cv_alphas) array, shape (n_folds, n_cv_alphas)

array, shape (n_l1_ratio, n_alpha, n_folds) array, shape (n_l1_ratio, n_alpha, n_folds)

array, shape (n_nonzero_coefs,) array, shape (n_nonzero_coefs,)

array, shape (n_params,) array, shape (n_params,)

array, shape (n_permutations,) array, shape (n_permutations,)

array, shape (n_query, self.n_neighbors) array, shape (n_query, self.n_neighbors)

array, shape (n_samples * (n_samples-1) / 2,) array, shape (n_samples * (n_samples-1) / 2,)

array, shape (n_samples, k) array, shape (n_samples, k)

array, shape (n_samples, n_classes) array, shape (n_samples, n_classes)

array, shape (n_samples, n_component) array, shape (n_samples, n_component)

array, shape (n_samples, n_components) array, shape (n_samples, n_components)

array, shape (n_samples, n_components) | None array, shape (n_samples, n_components) | None

array, shape (n_samples, n_features) array, shape (n_samples, n_features)

array, shape (n_samples, n_features) or (n_samples, n_samples) array, shape (n_samples, n_features) or (n_samples, n_samples)

array, shape (n_samples, n_neighbors) array, shape (n_samples, n_neighbors)

array, shape (n_samples, n_samples) array, shape (n_samples, n_samples)

array, shape (n_samples,) array, shape (n_samples,)

array, shape (n_samples,) of arrays array, shape (n_samples,) of arrays

array, shape (n_samples,) or (n_samples, n_targets) array, shape (n_samples,) or (n_samples, n_targets)

array, shape (n_samples,), optional array, shape (n_samples,), optional

array, shape (n_samples_X, n_features) array, shape (n_samples_X, n_features)

array, shape (n_samples_X, n_kernels) array, shape (n_samples_X, n_kernels)

array, shape (n_samples_X, n_samples_X, n_dims, n_kernels) array, shape (n_samples_X, n_samples_X, n_dims, n_kernels)

array, shape (n_samples_X, n_samples_Y) array, shape (n_samples_X, n_samples_Y)

array, shape (n_samples_X, n_samples_Y, n_kernels) array, shape (n_samples_X, n_samples_Y, n_kernels)

array, shape (n_samples_X,) array, shape (n_samples_X,)

array, shape (n_samples_Y, n_features), (optional, default=None) array, shape (n_samples_Y, n_features), (optional, default=None)

array, shape (n_tasks, n_features) array, shape (n_tasks, n_features)

array, shape (n_tasks,) array, shape (n_tasks,)

array, shape (n_ticks, n_cv_folds) array, shape (n_ticks, n_cv_folds)

array, shape (n_unique_ticks,), dtype int array, shape (n_unique_ticks,), dtype int

array, shape (nsamples,) array, shape (nsamples,)

array, shape = (n_samples, ) array, shape = (n_samples, )

array, shape = (image_height, image_width) or array, shape = (image_height, image_width) or

array, shape = (n_features) array, shape = (n_features)

array, shape = (n_features, n_features) array, shape = (n_features, n_features)

array, shape = (n_features,) array, shape = (n_features,)

array, shape = (n_kernel_params,), optional array, shape = (n_kernel_params,), optional

array, shape = (n_patches, patch_height, patch_width) or array, shape = (n_patches, patch_height, patch_width) or

array, shape = (n_samples, ), dtype = bool array, shape = (n_samples, ), dtype = bool

array, shape = (n_samples, [n_output_dims]) array, shape = (n_samples, [n_output_dims])

array, shape = (n_samples, image_height, image_width) or array, shape = (n_samples, image_height, image_width) or

array, shape = (n_samples, n_samples), optional array, shape = (n_samples, n_samples), optional

array, shape = (n_samples,) array, shape = (n_samples,)

array, shape = (n_samples,) component memberships array, shape = (n_samples,) component memberships

array, shape = (n_samples,), optional array, shape = (n_samples,), optional

array, shape = (n_samples_X, [n_output_dims], n_samples) array, shape = (n_samples_X, [n_output_dims], n_samples)

array, shape = (n_unique_ticks,), dtype int array, shape = (n_unique_ticks,), dtype int

array, shape = [1, n_SV] array, shape = [1, n_SV]

array, shape = [1, n_features] array, shape = [1, n_features]

array, shape = [1, n_features] if n_classes == 2 else [n_classes, n_features] array, shape = [1, n_features] if n_classes == 2 else [n_classes, n_features]

array, shape = [1,] array, shape = [1,]

array, shape = [14, 1592, 1212] array, shape = [14, 1592, 1212]

array, shape = [1] array, shape = [1]

array, shape = [1] if n_classes == 2 else [n_classes] array, shape = [1] if n_classes == 2 else [n_classes]

array, shape = [>2] array, shape = [>2]

array, shape = [n_classes] array, shape = [n_classes]

array, shape = [n] array, shape = [n]

array, shape = [n_class * (n_class-1) / 2] array, shape = [n_class * (n_class-1) / 2]

array, shape = [n_class-1, n_SV] array, shape = [n_class-1, n_SV]

array, shape = [n_class-1, n_features] array, shape = [n_class-1, n_features]

array, shape = [n_classes, n_classes] array, shape = [n_classes, n_classes]

array, shape = [n_classes, n_features] array, shape = [n_classes, n_features]

array, shape = [n_classes,n_features] array, shape = [n_classes,n_features]

array, shape = [n_classes] array, shape = [n_classes]

array, shape = [n_classes], optional array, shape = [n_classes], optional

array, shape = [n_core_samples, n_features] array, shape = [n_core_samples, n_features]

array, shape = [n_core_samples] array, shape = [n_core_samples]

array, shape = [n_estimators] array, shape = [n_estimators]

array, shape = [n_features, n_grid] array, shape = [n_features, n_grid]

array, shape = [n_features, n_reg_parameter] array, shape = [n_features, n_reg_parameter]

array, shape = [n_features,] array, shape = [n_features,]

array, shape = [n_features] array, shape = [n_features]

array, shape = [n_features] if n_classes == 2 else [n_classes, n_features] array, shape = [n_features] if n_classes == 2 else [n_classes, n_features]

array, shape = [n_features] or [n_targets, n_features] array, shape = [n_features] or [n_targets, n_features]

array, shape = [n_features], or None array, shape = [n_features], or None

array, shape = [n_labels] array, shape = [n_labels]

array, shape = [n_labels], optional array, shape = [n_labels], optional

array, shape = [n_labels], optional (default=None) array, shape = [n_labels], optional (default=None)

array, shape = [n_observations,] array, shape = [n_observations,]

array, shape = [n_samples, k] array, shape = [n_samples, k]

array, shape = [n_samples, n_alphas] or shape = [n_samples, n_targets, n_alphas], optional array, shape = [n_samples, n_alphas] or shape = [n_samples, n_targets, n_alphas], optional

array, shape = [n_samples, n_alphas] or shape = [n_samples, n_responses, n_alphas], optional array, shape = [n_samples, n_alphas] or shape = [n_samples, n_responses, n_alphas], optional

array, shape = [n_samples, n_classes] array, shape = [n_samples, n_classes]

array, shape = [n_samples, n_classes] or [n_samples,] array, shape = [n_samples, n_classes] or [n_samples,]

array, shape = [n_samples, n_classes] or [n_samples] array, shape = [n_samples, n_classes] or [n_samples]

array, shape = [n_samples, n_clusters] or [n_clusters] array, shape = [n_samples, n_clusters] or [n_clusters]

array, shape = [n_samples, n_components] array, shape = [n_samples, n_components]

array, shape = [n_samples, n_features] array, shape = [n_samples, n_features]

array, shape = [n_samples, n_labels] array, shape = [n_samples, n_labels]

array, shape = [n_samples] array, shape = [n_samples]

array, shape = [n_samples] or [n_samples, n_outputs] array, shape = [n_samples] or [n_samples, n_outputs]

array, shape = [n_samples] or [n_samples, n_classes] array, shape = [n_samples] or [n_samples, n_classes]

array, shape = [n_samples] or [n_samples, n_outputs] array, shape = [n_samples] or [n_samples, n_outputs]

array, shape = [n_samples] or [n_samples, n_targets] array, shape = [n_samples] or [n_samples, n_targets]

array, shape = [n_subpopulation, n_features + intercept] array, shape = [n_subpopulation, n_features + intercept]

array, shape = [n_subpopulation, n_subsamples] array, shape = [n_subpopulation, n_subsamples]

array, shape = [n_thresholds + 1] array, shape = [n_thresholds + 1]

array, shape = [n_thresholds <= len(np.unique(probas_pred))] array, shape = [n_thresholds <= len(np.unique(probas_pred))]

array, shape = [n_thresholds <= len(np.unique(y_score))] array, shape = [n_thresholds <= len(np.unique(y_score))]

array, shape = [n_thresholds] array, shape = [n_thresholds]

array, shape = [p, n_components] array, shape = [p, n_components]

array, shape = [q, n_components] array, shape = [q, n_components]

array, shape = image_size array, shape = image_size

array, shape [n_classes] array, shape [n_classes]

array, shape [n_features, n_classes] array, shape [n_features, n_classes]

array, shape [n_samples, k] array, shape [n_samples, k]

array, shape [n_samples,] array, shape [n_samples,]

array, shape [n_samples] if axis=1 else [n_features] array, shape [n_samples] if axis=1 else [n_features]

array, shape (n_folds, len(Cs_), n_features) or (n_folds, len(Cs_), n_features + 1) array, shape (n_folds, len(Cs_), n_features) or (n_folds, len(Cs_), n_features + 1)

array, shape ~ [n_grid] array, shape ~ [n_grid]

array, shape(k, n_features) array, shape(k, n_features)

array, shape(n_cs,) array, shape(n_cs,)

array, shape(n_samples, n_features) array, shape(n_samples, n_features)

array, shape=(n_classes, n_points) array, shape=(n_classes, n_points)

array, shape=(n_components, n_components) array, shape=(n_components, n_components)

array, shape=(n_components, n_samples) array, shape=(n_components, n_samples)

array, shape=(n_features,) array, shape=(n_features,)

array, shape=(n_samples, n_components) array, shape=(n_samples, n_components)

array, shape=(n_samples,) array, shape=(n_samples,)

array, shape=[n_clusters, n_features] array, shape=[n_clusters, n_features]

array, shape=[n_samples, n_features] or [n_features] array, shape=[n_samples, n_features] or [n_features]

array, shape=[n_samples, n_features], optional array, shape=[n_samples, n_features], optional

array, shape=[n_samples] array, shape=[n_samples]

array-like array-like

array-like of float, shape = (n_samples, n_classes) array-like of float, shape = (n_samples, n_classes)

array-like of float, shape = (n_samples, n_classes) or (n_samples,) array-like of float, shape = (n_samples, n_classes) or (n_samples,)

array-like of floats, shape (n_samples, n_features) array-like of floats, shape (n_samples, n_features)

array-like of int array-like of int

array-like of int with shape (n_samples,) array-like of int with shape (n_samples,)

array-like of shape (n_samples, n_estimators), or int. array-like of shape (n_samples, n_estimators), or int.

array-like of shape (n_samples, n_features) array-like of shape (n_samples, n_features)

array-like of shape (n_samples,) array-like of shape (n_samples,)

array-like of shape (n_samples_X, n_features) array-like of shape (n_samples_X, n_features)

array-like of shape = (n_outputs) or string in ['raw_values', array-like of shape = (n_outputs) or string in ['raw_values',

array-like of shape = (n_samples) array-like of shape = (n_samples)

array-like of shape = (n_samples) or (n_samples, n_outputs) array-like of shape = (n_samples) or (n_samples, n_outputs)

array-like of shape = (n_samples), optional array-like of shape = (n_samples), optional

array-like of shape = (n_samples, n_outputs) array-like of shape = (n_samples, n_outputs)

array-like of shape = (n_samples,), optional array-like of shape = (n_samples,), optional

array-like of shape = [n_samples, n_features] array-like of shape = [n_samples, n_features]

array-like of shape = [n_samples] array-like of shape = [n_samples]

array-like of shape = [n_samples] or None array-like of shape = [n_samples] or None

array-like of shape = [n_samples], default None array-like of shape = [n_samples], default None

array-like of shape = [n_samples], optional array-like of shape = [n_samples], optional

array-like of shape [n_classes] array-like of shape [n_classes]

array-like of shape [n_classes] (optional) array-like of shape [n_classes] (optional)

array-like of shape [n_samples, n_features] array-like of shape [n_samples, n_features]

array-like of shape [n_samples] array-like of shape [n_samples]

array-like of shape [n_samples] (optional) array-like of shape [n_samples] (optional)

array-like of shape at least 2D array-like of shape at least 2D

array-like or BallTree, shape = [n_samples, n_features] array-like or BallTree, shape = [n_samples, n_features]

array-like or None array-like or None

array-like or None (default is None) array-like or None (default is None)

array-like or callable, optional array-like or callable, optional

array-like or int array-like or int

array-like or int. array-like or int.

array-like or label indicator matrix array-like or label indicator matrix

array-like or list of array-like of shape = [n_samples, n_classes] array-like or list of array-like of shape = [n_samples, n_classes]

array-like or list of array-lke of shape = [n_samples, n_classes] array-like or list of array-lke of shape = [n_samples, n_classes]

array-like or sparse matrix array-like or sparse matrix

array-like or sparse matrix of shape = [n_samples, n_features] array-like or sparse matrix of shape = [n_samples, n_features]

array-like or sparse matrix, [n_samples, n_features] array-like or sparse matrix, [n_samples, n_features]

array-like or sparse matrix, shape (n_samples, n_features) array-like or sparse matrix, shape (n_samples, n_features)

array-like or sparse matrix, shape (n_samples, sum_n_components) array-like or sparse matrix, shape (n_samples, sum_n_components)

array-like or sparse matrix, shape = [n_samples, n_features] array-like or sparse matrix, shape = [n_samples, n_features]

array-like or sparse matrix, shape [n_samples, n_encoded_features] array-like or sparse matrix, shape [n_samples, n_encoded_features]

array-like or sparse matrix, shape [n_samples, n_features] array-like or sparse matrix, shape [n_samples, n_features]

array-like or sparse matrix, shape: (n_samples, n_samples) array-like or sparse matrix, shape: (n_samples, n_samples)

array-like or sparse matrix, shape=(n_samples, n_features) array-like or sparse matrix, shape=(n_samples, n_features)

array-like or string in ['raw_values', uniform_average', array-like or string in ['raw_values', uniform_average',

array-like with shape (n_samples, ) array-like with shape (n_samples, )

array-like, array-like,

array-like, (n_features,) array-like, (n_features,)

array-like, (n_samples, n_features), optional array-like, (n_samples, n_features), optional

array-like, [n_samples] array-like, [n_samples]

array-like, default=None array-like, default=None

array-like, dtype=int array-like, dtype=int

array-like, dtype=int32, shape = [n_class] array-like, dtype=int32, shape = [n_class]

array-like, of length n_samples array-like, of length n_samples

array-like, optional array-like, optional

array-like, optional (default=None) array-like, optional (default=None)

array-like, optional, default: None array-like, optional, default: None

array-like, optional. array-like, optional.

array-like, shape (n_samples, n_features) array-like, shape (n_samples, n_features)

array-like, shape (M, N) array-like, shape (M, N)

array-like, shape (M, N) or (M, ) array-like, shape (M, N) or (M, )

array-like, shape (n_samples, n_features) array-like, shape (n_samples, n_features)

array-like, shape (n_samples,) array-like, shape (n_samples,)

array-like, shape (n_alphas,) array-like, shape (n_alphas,)

array-like, shape (n_classes, n_features) array-like, shape (n_classes, n_features)

array-like, shape (n_classes,) array-like, shape (n_classes,)

array-like, shape (n_classes,), optional array-like, shape (n_classes,), optional

array-like, shape (n_classes,), optional (default=None) array-like, shape (n_classes,), optional (default=None)

array-like, shape (n_cols,) array-like, shape (n_cols,)

array-like, shape (n_column_clusters, n_columns) array-like, shape (n_column_clusters, n_columns)

array-like, shape (n_components, ), optional array-like, shape (n_components, ), optional

array-like, shape (n_components, n_features) array-like, shape (n_components, n_features)

array-like, shape (n_components, n_features), optional array-like, shape (n_components, n_features), optional

array-like, shape (n_components, n_features, n_features) array-like, shape (n_components, n_features, n_features)

array-like, shape (n_components, n_samples) array-like, shape (n_components, n_samples)

array-like, shape (n_components,) array-like, shape (n_components,)

array-like, shape (n_features, ) array-like, shape (n_features, )

array-like, shape (n_features, n_features) array-like, shape (n_features, n_features)

array-like, shape (n_features,) array-like, shape (n_features,)

array-like, shape (n_features,), default None array-like, shape (n_features,), default None

array-like, shape (n_features,), optional array-like, shape (n_features,), optional

array-like, shape (n_nodes-1, 2) array-like, shape (n_nodes-1, 2)

array-like, shape (n_params,) array-like, shape (n_params,)

array-like, shape (n_query, n_features), or (n_query, n_indexed) if metric == 'precomputed' array-like, shape (n_query, n_features), or (n_query, n_indexed) if metric == 'precomputed'

array-like, shape (n_row_clusters, n_rows) array-like, shape (n_row_clusters, n_rows)

array-like, shape (n_rows,) array-like, shape (n_rows,)

array-like, shape (n_samples) or (n_samples, n_features), optional array-like, shape (n_samples) or (n_samples, n_features), optional

array-like, shape (n_samples, ) array-like, shape (n_samples, )

array-like, shape (n_samples, ...), optional array-like, shape (n_samples, ...), optional

array-like, shape (n_samples, n_class * (n_class-1) / 2) array-like, shape (n_samples, n_class * (n_class-1) / 2)

array-like, shape (n_samples, n_classes ) array-like, shape (n_samples, n_classes )

array-like, shape (n_samples, n_classes * (n_classes-1) / 2) array-like, shape (n_samples, n_classes * (n_classes-1) / 2)

array-like, shape (n_samples, n_classes) array-like, shape (n_samples, n_classes)

array-like, shape (n_samples, n_classifiers) array-like, shape (n_samples, n_classifiers)

array-like, shape (n_samples, n_components) array-like, shape (n_samples, n_components)

array-like, shape (n_samples, n_dim) array-like, shape (n_samples, n_dim)

array-like, shape (n_samples, n_dimensions) array-like, shape (n_samples, n_dimensions)

array-like, shape (n_samples, n_features) array-like, shape (n_samples, n_features)

array-like, shape (n_samples, n_features) or (n_samples, n_samples) array-like, shape (n_samples, n_features) or (n_samples, n_samples)

array-like, shape (n_samples, n_features), default=None array-like, shape (n_samples, n_features), default=None

array-like, shape (n_samples, n_neighbors) array-like, shape (n_samples, n_neighbors)

array-like, shape (n_samples, n_neighbors, n_dim) array-like, shape (n_samples, n_neighbors, n_dim)

array-like, shape (n_samples, n_outputs) array-like, shape (n_samples, n_outputs)

array-like, shape (n_samples, n_samples) array-like, shape (n_samples, n_samples)

array-like, shape (n_samples,) array-like, shape (n_samples,)

array-like, shape (n_samples,) optional array-like, shape (n_samples,) optional

array-like, shape (n_samples,) or (n_samples, n_classes) array-like, shape (n_samples,) or (n_samples, n_classes)

array-like, shape (n_samples,) or (n_samples, n_outputs) array-like, shape (n_samples,) or (n_samples, n_outputs)

array-like, shape (n_samples,) or (n_samples, n_targets) array-like, shape (n_samples,) or (n_samples, n_targets)

array-like, shape (n_samples,) or (n_samples, n_targets), optional array-like, shape (n_samples,) or (n_samples, n_targets), optional

array-like, shape (n_samples,) or float, optional array-like, shape (n_samples,) or float, optional

array-like, shape (n_samples,), optional array-like, shape (n_samples,), optional

array-like, shape (n_samples,), optional (default=None) array-like, shape (n_samples,), optional (default=None)

array-like, shape (n_samples-1, 2) array-like, shape (n_samples-1, 2)

array-like, shape (n_samples_2, ), optional array-like, shape (n_samples_2, ), optional

array-like, shape (n_subsample,), or None array-like, shape (n_subsample,), or None

array-like, shape (n_targets,) array-like, shape (n_targets,)

array-like, shape (n_test_samples,) array-like, shape (n_test_samples,)

array-like, shape (n_ticks,), dtype float or int array-like, shape (n_ticks,), dtype float or int

array-like, shape (n_train_samples,) array-like, shape (n_train_samples,)

array-like, shape (n_values,) array-like, shape (n_values,)

array-like, shape (number of Gaussians,) array-like, shape (number of Gaussians,)

array-like, shape (number of nodes of all layers,) array-like, shape (number of nodes of all layers,)

array-like, shape (rank, n_classes - 1) array-like, shape (rank, n_classes - 1)

array-like, shape = (n_classes,) array-like, shape = (n_classes,)

array-like, shape = (n_kernel_params,) or None array-like, shape = (n_kernel_params,) or None

array-like, shape = (n_kernel_params,) or none array-like, shape = (n_kernel_params,) or none

array-like, shape = (n_samples) or (n_samples, n_outputs) array-like, shape = (n_samples) or (n_samples, n_outputs)

array-like, shape = (n_samples) or None array-like, shape = (n_samples) or None

array-like, shape = (n_samples, [n_output_dims]) array-like, shape = (n_samples, [n_output_dims])

array-like, shape = (n_samples, n_classes) array-like, shape = (n_samples, n_classes)

array-like, shape = (n_samples, n_components) array-like, shape = (n_samples, n_components)

array-like, shape = (n_samples, n_features) array-like, shape = (n_samples, n_features)

array-like, shape = (n_samples, n_samples) array-like, shape = (n_samples, n_samples)

array-like, shape = (n_samples,) array-like, shape = (n_samples,)

array-like, shape = (n_samples,) or (n_samples, n_outputs) array-like, shape = (n_samples,) or (n_samples, n_outputs)

array-like, shape = (n_samples,), optional array-like, shape = (n_samples,), optional

array-like, shape = (n_samples_X, n_features) array-like, shape = (n_samples_X, n_features)

array-like, shape = [nSV, n_features] array-like, shape = [nSV, n_features]

array-like, shape = [n_SV, n_features] array-like, shape = [n_SV, n_features]

array-like, shape = [n_SV] array-like, shape = [n_SV]

array-like, shape = [n_classes, n_features] array-like, shape = [n_classes, n_features]

array-like, shape = [n_classes] array-like, shape = [n_classes]

array-like, shape = [n_classes] (default=None) array-like, shape = [n_classes] (default=None)

array-like, shape = [n_classifiers], optional (default=`None`) array-like, shape = [n_classifiers], optional (default=`None`)

array-like, shape = [n_features, n_features] array-like, shape = [n_features, n_features]

array-like, shape = [n_observations, n_features] array-like, shape = [n_observations, n_features]

array-like, shape = [n_predictions] array-like, shape = [n_predictions]

array-like, shape = [n_samples, n_classes] array-like, shape = [n_samples, n_classes]

array-like, shape = [n_samples, n_features] array-like, shape = [n_samples, n_features]

array-like, shape = [n_samples, n_features] or [n_features] array-like, shape = [n_samples, n_features] or [n_features]

array-like, shape = [n_samples, n_features], optional array-like, shape = [n_samples, n_features], optional

array-like, shape = [n_samples, n_targets] array-like, shape = [n_samples, n_targets]

array-like, shape = [n_samples, n_transformed_features] array-like, shape = [n_samples, n_transformed_features]

array-like, shape = [n_samples] array-like, shape = [n_samples]

array-like, shape = [n_samples] (default=None) array-like, shape = [n_samples] (default=None)

array-like, shape = [n_samples] or None array-like, shape = [n_samples] or None

array-like, shape = [n_samples] or [n_samples, n_output], optional array-like, shape = [n_samples] or [n_samples, n_output], optional

array-like, shape = [n_samples] or [n_samples, n_outputs] array-like, shape = [n_samples] or [n_samples, n_outputs]

array-like, shape = [n_samples] or [n_samples, n_targets] array-like, shape = [n_samples] or [n_samples, n_targets]

array-like, shape = [n_samples], (default=None) array-like, shape = [n_samples], (default=None)

array-like, shape = [n_samples], optional array-like, shape = [n_samples], optional

array-like, shape = [n_samples_1], optional array-like, shape = [n_samples_1], optional

array-like, shape [n_samples, n_components] array-like, shape [n_samples, n_components]

array-like, shape [n_samples, n_feature] array-like, shape [n_samples, n_feature]

array-like, shape [n_samples, n_features] array-like, shape [n_samples, n_features]

array-like, shape [n_samples, n_outputs] array-like, shape [n_samples, n_outputs]

array-like, shape [n_samples] array-like, shape [n_samples]

array-like, shape(n_samples,) optional array-like, shape(n_samples,) optional

array-like, shape: (M, N) or (M, ), optional: array-like, shape: (M, N) or (M, ), optional:

array-like, shape: (n_features,) array-like, shape: (n_features,)

array-like, shape: (n_samples, n_clusters) array-like, shape: (n_samples, n_clusters)

array-like, shape: (n_samples, n_samples) array-like, shape: (n_samples, n_samples)

array-like, shape: (n_samples,) array-like, shape: (n_samples,)

array-like, shape=(n_features,) array-like, shape=(n_features,)

array-like, shape=(n_points, len(target_variables)) array-like, shape=(n_points, len(target_variables))

array-like, shape=(n_samples, n_feature) array-like, shape=(n_samples, n_feature)

array-like, shape=(n_samples, n_features) array-like, shape=(n_samples, n_features)

array-like, shape=(n_samples,) array-like, shape=(n_samples,)

array-like, shape=(n_samples,), optional, default: None array-like, shape=(n_samples,), optional, default: None

array-like, shape=[n_outputs] or 'random', optional array-like, shape=[n_outputs] or 'random', optional

array-like, shape=[n_samples, n_clusters] or [n_clusters,] array-like, shape=[n_samples, n_clusters] or [n_clusters,]

array-like, shape=[n_samples, n_features] array-like, shape=[n_samples, n_features]

array-like, shape=[n_seeds, n_features] or None array-like, shape=[n_seeds, n_features] or None

array-like, size (n_classes,), optional (default=None) array-like, size (n_classes,), optional (default=None)

array-like, size=[n_classes,], optional (default=None) array-like, size=[n_classes,], optional (default=None)

array-like, sparse matrix array-like, sparse matrix

array-like, sparse matrix or iterable array-like, sparse matrix or iterable

array-like, sparse matrix or list array-like, sparse matrix or list

array-like, sparse-matrix, list, pandas.DataFrame, pandas.Series. array-like, sparse-matrix, list, pandas.DataFrame, pandas.Series.

array-like, type boolean, shape (n_samples,) array-like, type boolean, shape (n_samples,)

array-like, with shape (n_samples,), optional array-like, with shape (n_samples,), optional

array_like array_like

array_like or sparse (CSR) matrix, shape (n_samples, n_features) array_like or sparse (CSR) matrix, shape (n_samples, n_features)

array_like or sparse matrix, shape (n_samples, n_features) array_like or sparse matrix, shape (n_samples, n_features)

array_like or sparse matrix, shape = [n_samples, n_features] array_like or sparse matrix, shape = [n_samples, n_features]

array_like, optional array_like, optional

array_like, optional (if eval_MSE == True) array_like, optional (if eval_MSE == True)

array_like, shape (n, n_features) array_like, shape (n, n_features)

array_like, shape (n_components, n_features) array_like, shape (n_components, n_features)

array_like, shape (n_features,) array_like, shape (n_features,)

array_like, shape (n_samples, ) or (n_samples, n_targets) array_like, shape (n_samples, ) or (n_samples, n_targets)

array_like, shape (n_samples, n_components) array_like, shape (n_samples, n_components)

array_like, shape (n_samples, n_features) array_like, shape (n_samples, n_features)

array_like, shape (n_samples,) array_like, shape (n_samples,)

array_like, shape = [n_samples, n_estimators, n_classes] array_like, shape = [n_samples, n_estimators, n_classes]

array_like, shape = [n_samples, n_estimators] array_like, shape = [n_samples, n_estimators]

array_like, shape = [n_samples, n_features] array_like, shape = [n_samples, n_features]

array_like, shape = [n_samples,] array_like, shape = [n_samples,]

array_like, shape = [n_samples] array_like, shape = [n_samples]

array_like, sparse matrix array_like, sparse matrix

array_like, sparse matrix (optional) array_like, sparse matrix (optional)

arrays with shape (n_samples * (n_samples - 1) / 2, 2) arrays with shape (n_samples * (n_samples - 1) / 2, 2)

attribute name(s) given as string or a list/tuple of strings attribute name(s) given as string or a list/tuple of strings

bool bool

bool (default True) bool (default True)

bool (default=False) bool (default=False)

bool (optional) bool (optional)

bool (optional, default=False) bool (optional, default=False)

bool array of shape [n_samples] bool array of shape [n_samples]

bool or 'auto' (optional) bool or 'auto' (optional)

bool or 'auto', optional (default='auto') bool or 'auto', optional (default='auto')

bool or 'auto', optional, default "auto" bool or 'auto', optional, default "auto"

bool or int, optional bool or int, optional

bool or integer bool or integer

bool, bool,

bool, (default=True) bool, (default=True)

bool, False by default bool, False by default

bool, default False bool, default False

bool, default True bool, default True

bool, default to False. bool, default to False.

bool, default: False bool, default: False

bool, default: True bool, default: True

bool, default=False bool, default=False

bool, default=False. bool, default=False.

bool, default=True bool, default=True

bool, optional bool, optional

bool, optional (default False) bool, optional (default False)

bool, optional (default: False) bool, optional (default: False)

bool, optional (default: None) bool, optional (default: None)

bool, optional (default: True) bool, optional (default: True)

bool, optional (default=False) bool, optional (default=False)

bool, optional (default=None) bool, optional (default=None)

bool, optional (default=True) bool, optional (default=True)

bool, optional default False bool, optional default False

bool, optional default=False bool, optional default=False

bool, optional default=True bool, optional default=True

bool, optional, default False bool, optional, default False

bool, optional, default True bool, optional, default True

bool, optional, default: False bool, optional, default: False

bool, optional, default=False bool, optional, default=False

bool, optional, default=True bool, optional, default=True

bool, optional. Default: False bool, optional. Default: False

boolean boolean

boolean (default False) boolean (default False)

boolean (default: False) boolean (default: False)

boolean (default: False), boolean (default: False),

boolean (default=False) boolean (default=False)

boolean (default=True) boolean (default=True)

boolean (optional), default True boolean (optional), default True

boolean optional boolean optional

boolean or "auto", optional boolean or "auto", optional

boolean or "auto", optional, default "auto" boolean or "auto", optional, default "auto"

boolean or integer, optional boolean or integer, optional

boolean or string, optional, default: True boolean or string, optional, default: True

boolean, boolean,

boolean, (True by default) boolean, (True by default)

boolean, (default True) boolean, (default True)

boolean, (default=True) boolean, (default=True)

boolean, True by default boolean, True by default

boolean, default = False boolean, default = False

boolean, default False boolean, default False

boolean, default True boolean, default True

boolean, default: False boolean, default: False

boolean, default: True boolean, default: True

boolean, default='warn' boolean, default='warn'

boolean, default=False boolean, default=False

boolean, default=False. boolean, default=False.

boolean, default=True boolean, default=True

boolean, defaults to False boolean, defaults to False

boolean, optional boolean, optional

boolean, optional (default = False) boolean, optional (default = False)

boolean, optional (default = True) boolean, optional (default = True)

boolean, optional (default: False) boolean, optional (default: False)

boolean, optional (default='deprecated') boolean, optional (default='deprecated')

boolean, optional (default=False) boolean, optional (default=False)

boolean, optional (default=True) boolean, optional (default=True)

boolean, optional, (default=False) boolean, optional, (default=False)

boolean, optional, (default=True) boolean, optional, (default=True)

boolean, optional, default False boolean, optional, default False

boolean, optional, default True boolean, optional, default True

boolean, optional, default True. boolean, optional, default True.

boolean, optional, default is True boolean, optional, default is True

boolean, optional, default: False boolean, optional, default: False

boolean, optional, default: True boolean, optional, default: True

boolean, optional, default=True boolean, optional, default=True

boolean, optional. boolean, optional.

boolean, optional. Defaults to True. boolean, optional. Defaults to True.

boolean, or integer boolean, or integer

boolean, or string default=True boolean, or string default=True

boolean, or string, default=True boolean, or string, default=True

bunch object, a dictionary with attribute access bunch object, a dictionary with attribute access

callable callable

callable or None callable or None

callable or None (default) callable or None (default)

callable or None, optional (default: None) callable or None, optional (default: None)

callable or None, optional, default: None callable or None, optional, default: None

callable or None. callable or None.

callable, callable,

callable, default empirical_covariance callable, default empirical_covariance

callable, default np.mean callable, default np.mean

callable, default='deprecated' callable, default='deprecated'

callable, optional callable, optional

callable, optional default=None callable, optional default=None

callable, returns shape [n_classes] callable, returns shape [n_classes]

callable, {all, any}, default all callable, {all, any}, default all

concrete LossFunction concrete LossFunction

csr sparse matrix, shape (n_samples, n_sample) csr sparse matrix, shape (n_samples, n_sample)

csr sparse matrix, shape (n_samples, n_samples) csr sparse matrix, shape (n_samples, n_samples)

decision tree regressor or classifier decision tree regressor or classifier

dense matrix, shape=(n_topics, n_features) dense matrix, shape=(n_topics, n_features)

dict dict

dict of float arrays of shape=(n_splits,) dict of float arrays of shape=(n_splits,)

dict of numpy (masked) ndarrays dict of numpy (masked) ndarrays

dict of scorer name -> float, optional dict of scorer name -> float, optional

dict of string to any dict of string to any

dict of string to sequence, or sequence of such dict of string to sequence, or sequence of such

dict or 'balanced', default: None dict or 'balanced', default: None

dict or 'balanced', optional dict or 'balanced', optional

dict or None dict or None

dict or None, optional dict or None, optional

dict or list of dictionaries dict or list of dictionaries

dict, 'balanced' or None dict, 'balanced' or None

dict, default: None dict, default: None

dict, keys=str, values=ndarray dict, keys=str, values=ndarray

dict, list of dicts, "balanced" or None, default=None dict, list of dicts, "balanced" or None, default=None

dict, list of dicts, "balanced", dict, list of dicts, "balanced",

dict, list of dicts, "balanced", "balanced_subsample" or None, optional (default=None) dict, list of dicts, "balanced", "balanced_subsample" or None, optional (default=None)

dict, list of dicts, "balanced", or None, optional dict, list of dicts, "balanced", or None, optional

dict, optional dict, optional

dict, optional (default = None) dict, optional (default = None)

dict, optional (default=None) dict, optional (default=None)

dict, {class_label: weight} or "balanced" or None, optional dict, {class_label: weight} or "balanced" or None, optional

dict-like object with the following attributes: dict-like object with the following attributes:

dictionary dictionary

dictionary, optional dictionary, optional

double double

double array_like double array_like

double array_like, optional double array_like, optional

double or None (default=None) double or None (default=None)

double or ndarray, optional double or ndarray, optional

double, default: 0. double, default: 0.

double, optional double, optional

double, optional, default 0.001 double, optional, default 0.001

double, optional, default 0.5 double, optional, default 0.5

dtype, optional, default int dtype, optional, default int

estimator estimator

estimator instance. estimator instance.

estimator object estimator object

estimator object implementing 'fit' estimator object implementing 'fit'

estimator object implementing 'fit' and 'predict' estimator object implementing 'fit' and 'predict'

estimator object or class estimator object or class

estimator object, or list, tuple or set of objects estimator object, or list, tuple or set of objects

estimator object. estimator object.

estimator supporting get/set_params estimator supporting get/set_params

exception or tuple of exception exception or tuple of exception

figure figure

file object file object

file object or string, optional (default='tree.dot') file object or string, optional (default='tree.dot')

float float

float (default 0.1), int, or None float (default 0.1), int, or None

float (default 0.2), int, or None float (default 0.2), int, or None

float (default: 0.5) float (default: 0.5)

float (default=0.9) float (default=0.9)

float (if average is not None) or array of float, , shape = [n_unique_labels] float (if average is not None) or array of float, , shape = [n_unique_labels]

float (if average is not None) or array of float, shape = [n_unique_labels] float (if average is not None) or array of float, shape = [n_unique_labels]

float (the lower the better) float (the lower the better)

float > 0, default: 1.0 float > 0, default: 1.0

float >= 0, default: 1.0 float >= 0, default: 1.0

float >= 0, optional (default .0) float >= 0, optional (default .0)

float array with shape (n_features,) float array with shape (n_features,)

float array with shape (n_samples,) float array with shape (n_samples,)

float array, shape (k, n_features) float array, shape (k, n_features)

float array, shape (n_samples,) float array, shape (n_samples,)

float between 0 and 1, optional (default=0.1) float between 0 and 1, optional (default=0.1)

float between 0 and 1, optional (default=0.9) float between 0 and 1, optional (default=0.9)

float between 0 and 1, optional (default=0.95) float between 0 and 1, optional (default=0.95)

float between 0.0 and 1.0, optional (default=0.5) float between 0.0 and 1.0, optional (default=0.5)

float in (0., 0.5), optional (default=0.1) float in (0., 0.5), optional (default=0.1)

float in (0., 1.), optional (default=None) float in (0., 1.), optional (default=None)

float in [0.0, 1.0] float in [0.0, 1.0]

float in range 0.0 - 1.0 float in range 0.0 - 1.0

float in range [0, 1], optional float in range [0, 1], optional

float in range [0.0, 1.0] or int, default=1 float in range [0.0, 1.0] or int, default=1

float in range [0.0, 1.0] or int, default=1.0 float in range [0.0, 1.0] or int, default=1.0

float in range ]0, 1] or 'auto', optional (default='auto') float in range ]0, 1] or 'auto', optional (default='auto')

float in range ]0, 1], optional (default='auto') float in range ]0, 1], optional (default='auto')

float ndarray with shape (k, n_features) float ndarray with shape (k, n_features)

float or None float or None

float or None, optional float or None, optional

float or None, optional (default=0.0) float or None, optional (default=0.0)

float or array of float, shape = [n_unique_labels] float or array of float, shape = [n_unique_labels]

float or array of floats float or array of floats

float or array of floats, optional float or array of floats, optional

float or array of shape [n_classes] float or array of shape [n_classes]

float or array of shape [n_outputs] float or array of shape [n_outputs]

float or array, shape (n_targets,) float or array, shape (n_targets,)

float or array, shape = [n_targets] float or array, shape = [n_targets]

float or array-like float or array-like

float or array-like of shape [n_reg_parameter], optional, default=1 float or array-like of shape [n_reg_parameter], optional, default=1

float or array-like of shape [n_samples] float or array-like of shape [n_samples]

float or array-like, optional float or array-like, optional

float or array-like, optional (default: 1e-10) float or array-like, optional (default: 1e-10)

float or array-like, shape (n_samples, n_features) float or array-like, shape (n_samples, n_features)

float or dense array-like, shape (n_components, n_features) float or dense array-like, shape (n_components, n_features)

float or dense array-like, shape (n_samples, n_components) float or dense array-like, shape (n_samples, n_components)

float or int depending on the feature selection mode float or int depending on the feature selection mode

float or int, float or int,

float or ndarray of floats float or ndarray of floats

float or numpy array of float in ]0,1[, optional (default=0.1) float or numpy array of float in ]0,1[, optional (default=0.1)

float or numpy array of shape (n_samples,) float or numpy array of shape (n_samples,)

float or numpy array of shape [n_samples] float or numpy array of shape [n_samples]

float or sequence of floats, optional (default=1.0) float or sequence of floats, optional (default=1.0)

float or string, default 'frobenius' float or string, default 'frobenius'

float | None, optional. float | None, optional.

float | array, shape (n_targets, n_features) float | array, shape (n_targets, n_features)

float | array, shape (n_targets,) float | array, shape (n_targets,)

float | array, shape = (n_targets,) float | array, shape = (n_targets,)

float, float,

float, 'aic', or 'bic', optional float, 'aic', or 'bic', optional

float, 0 < support_fraction < 1 float, 0 < support_fraction < 1

float, 0 <= shrinkage <= 1 float, 0 <= shrinkage <= 1

float, 0 <= shrinkage <= 1, default 0.1 float, 0 <= shrinkage <= 1, default 0.1

float, 1. by default float, 1. by default

float, 1.0 by default float, 1.0 by default

float, array of shape [n_features] or None, optional (default=0.0) float, array of shape [n_features] or None, optional (default=0.0)

float, array of shape [n_features] or None, optional (default=1.0) float, array of shape [n_features] or None, optional (default=1.0)

float, default 0.0001 float, default 0.0001

float, default 0.3 float, default 0.3

float, default 0.5 float, default 0.5

float, default 0.9 float, default 0.9

float, default 1 float, default 1

float, default 1. float, default 1.

float, default 1e-3 float, default 1e-3

float, default 1e-5 float, default 1e-5

float, default None float, default None

float, default: 0.0 float, default: 0.0

float, default: 0.01 float, default: 0.01

float, default: 1 float, default: 1

float, default: 1.0 float, default: 1.0

float, default: 1e-4 float, default: 1e-4

float, default=0 float, default=0

float, default=0.1 float, default=0.1

float, default=1 float, default=1

float, default=1. float, default=1.

float, default=1/n_features float, default=1/n_features

float, default=3 float, default=3

float, default=None float, default=None

float, defaults to 1e-3. float, defaults to 1e-3.

float, defaults to 1e-6. float, defaults to 1e-6.

float, greater than 1.0, default 1.35 float, greater than 1.0, default 1.35

float, int, None, default=0.1 float, int, None, default=0.1

float, int, None, optional float, int, None, optional

float, int, or None (default is None) float, int, or None (default is None)

float, int, or None, default None float, int, or None, default None

float, int, or None, default is None float, int, or None, default is None

float, int, or None, default=None float, int, or None, default=None

float, optinal (default = 1.0) float, optinal (default = 1.0)

float, optional float, optional

float, optional (0.0 by default) float, optional (0.0 by default)

float, optional (default = 0.9) float, optional (default = 0.9)

float, optional (default = 1.0) float, optional (default = 1.0)

float, optional (default = None) float, optional (default = None)

float, optional (default: 0.01) float, optional (default: 0.01)

float, optional (default: 12.0) float, optional (default: 12.0)

float, optional (default: 1e-7) float, optional (default: 1e-7)

float, optional (default: 200.0) float, optional (default: 200.0)

float, optional (default: 30) float, optional (default: 30)

float, optional (default='auto') float, optional (default='auto')

float, optional (default=0.) float, optional (default=0.)

float, optional (default=0.0) float, optional (default=0.0)

float, optional (default=0.01) float, optional (default=0.01)

float, optional (default=0.1) float, optional (default=0.1)

float, optional (default=0.5) float, optional (default=0.5)

float, optional (default=0.7) float, optional (default=0.7)

float, optional (default=1) float, optional (default=1)

float, optional (default=1.) float, optional (default=1.)

float, optional (default=1.0) float, optional (default=1.0)

float, optional (default=10.) float, optional (default=10.)

float, optional (default=1e-1) float, optional (default=1e-1)

float, optional (default=1e-3) float, optional (default=1e-3)

float, optional (default=1e-4) float, optional (default=1e-4)

float, optional (default=1e-9) float, optional (default=1e-9)

float, optional (default=None) float, optional (default=None)

float, optional, (default 1.0e-4) float, optional, (default 1.0e-4)

float, optional, default 0.0001 float, optional, default 0.0001

float, optional, default 0.1 float, optional, default 0.1

float, optional, default 0.5 float, optional, default 0.5

float, optional, default 0.9 float, optional, default 0.9

float, optional, default 0.999 float, optional, default 0.999

float, optional, default 1.0e-4 float, optional, default 1.0e-4

float, optional, default 1.e-3 float, optional, default 1.e-3

float, optional, default 1e-4 float, optional, default 1e-4

float, optional, default 1e-8 float, optional, default 1e-8

float, optional, default: 0.5 float, optional, default: 0.5

float, optional, default: 1e-3 float, optional, default: 1e-3

float, optional, default=0.0 float, optional, default=0.0

float, optional, default=0.25 float, optional, default=0.25

float, optional, default=0.5 float, optional, default=0.5

float, optional, default=0.75 float, optional, default=0.75

float, optional, default=1e-3 float, optional, default=1e-3

float, string in {'frobenius', 'kullback-leibler', 'itakura-saito'} float, string in {'frobenius', 'kullback-leibler', 'itakura-saito'}

float, within (0.0, 1.0), optional (default: 0.8) float, within (0.0, 1.0), optional (default: 0.8)

float. float.

float64 array-like or CSR sparse matrix, shape (n_samples, n_features) float64 array-like or CSR sparse matrix, shape (n_samples, n_features)

function function

function or callable function or callable

function, optional function, optional

generator of array of shape = [n_samples] generator of array of shape = [n_samples]

generator of array, shape = [n_samples, k] generator of array, shape = [n_samples, k]

generator of array, shape = [n_samples] generator of array, shape = [n_samples]

instance instance

instance BaseEstimator instance BaseEstimator

int int

int (0 by default) int (0 by default)

int (>= 1) or float ([0, 1]), optional int (>= 1) or float ([0, 1]), optional

int (default 10) int (default 10)

int (default 5) int (default 5)

int (default = 10) int (default = 10)

int (default = 4) int (default = 4)

int (default = 5) int (default = 5)

int (default = 50) int (default = 50)

int (default is 10) int (default is 10)

int (default: 0) int (default: 0)

int (default: 1) int (default: 1)

int (default=1) int (default=1)

int (default=100) int (default=100)

int (either 0 or 1) int (either 0 or 1)

int (if average is not None) or array of int, shape = [n_unique_labels] int (if average is not None) or array of int, shape = [n_unique_labels]

int (optional) int (optional)

int (optional, default:0) int (optional, default:0)

int (read-only) int (read-only)

int < p int < p

int >= 0, or 'auto', (default 'auto') int >= 0, or 'auto', (default 'auto')

int array of shape(n) int array of shape(n)

int array, shape = (n_samples,) int array, shape = (n_samples,)

int array, shape = [n_samples] int array, shape = [n_samples]

int or "all", optional, default=10 int or "all", optional, default=10

int or 'auto' (default is 'auto') int or 'auto' (default is 'auto')

int or 'auto', optional (default = 'auto') int or 'auto', optional (default = 'auto')

int or None int or None

int or None (default=None) int or None (default=None)

int or None, (default=None) int or None, (default=None)

int or None, default=None int or None, default=None

int or None, optional (default=None) int or None, optional (default=None)

int or array of shape [n_centers, n_features], optional int or array of shape [n_centers, n_features], optional

int or array-like int or array-like

int or float or array of shape = [n_outputs] int or float or array of shape = [n_outputs]

int or float, optional (default="auto") int or float, optional (default="auto")

int or float, optional (default=1) int or float, optional (default=1)

int or float, optional (default=1.0) int or float, optional (default=1.0)

int or float, optional (default=None) int or float, optional (default=None)

int or list int or list

int or ndarray int or ndarray

int or numpy array of int greater than 0, int or numpy array of int greater than 0,

int or numpy array of int, int or numpy array of int,

int or str or array of shape = [n_outputs] int or str or array of shape = [n_outputs]

int or str, default=None int or str, default=None

int | None int | None

int | array-like, shape (n_cs,) int | array-like, shape (n_cs,)

int | array-like, shape (n_targets,) int | array-like, shape (n_targets,)

int | float int | float

int, int,

int, (default 2) int, (default 2)

int, (default 2). int, (default 2).

int, (default=0) int, (default=0)

int, (default=1000) int, (default=1000)

int, 0.1 * n_features by default int, 0.1 * n_features by default

int, 1000 by default int, 1000 by default

int, > n_samples / 2 int, > n_samples / 2

int, None int, None

int, None by default int, None by default

int, RandomState instance or None, optional (default None) int, RandomState instance or None, optional (default None)

int, RandomState instance or None, optional (default: None) int, RandomState instance or None, optional (default: None)

int, RandomState instance or None, optional (default=0) int, RandomState instance or None, optional (default=0)

int, RandomState instance or None, optional (default=None) int, RandomState instance or None, optional (default=None)

int, RandomState instance or None, optional, default = None int, RandomState instance or None, optional, default = None

int, RandomState instance or None, optional, default None int, RandomState instance or None, optional, default None

int, RandomState instance or None, optional, default: None int, RandomState instance or None, optional, default: None

int, RandomState instance or None, optional, default=None int, RandomState instance or None, optional, default=None

int, RandomState instance or None. default to None int, RandomState instance or None. default to None

int, [(n + p + 1)/2] < n_support < n int, [(n + p + 1)/2] < n_support < n

int, 0.1 * n_features by default int, 0.1 * n_features by default

int, cross-validation generator or an iterable, optional int, cross-validation generator or an iterable, optional

int, cross-validation generator or an iterable, optional (default=None) int, cross-validation generator or an iterable, optional (default=None)

int, default 0 int, default 0

int, default 1 int, default 1

int, default 10 int, default 10

int, default 100 int, default 100

int, default 2 int, default 2

int, default 3 int, default 3

int, default 300 int, default 300

int, default 50 int, default 50

int, default = 2 int, default = 2

int, default None int, default None

int, default to 0. int, default to 0.

int, default to 10. int, default to 10.

int, default: 0 int, default: 0

int, default: 1 int, default: 1

int, default: 10 int, default: 10

int, default: 100 int, default: 100

int, default: 300 int, default: 300

int, default=0 int, default=0

int, default=1 int, default=1

int, default=1.0 int, default=1.0

int, default=10 int, default=10

int, default=100 int, default=100

int, default=1000 int, default=1000

int, default=2 int, default=2

int, default=3 int, default=3

int, default=5 int, default=5

int, default=5e8 int, default=5e8

int, default=None int, default=None

int, defaults to 1. int, defaults to 1.

int, defaults to 100. int, defaults to 100.

int, float, None or string int, float, None or string

int, float, optional (default=1) int, float, optional (default=1)

int, float, optional (default=2) int, float, optional (default=2)

int, float, string or None, optional (default="auto") int, float, string or None, optional (default="auto")

int, float, string or None, optional (default=None) int, float, string or None, optional (default=None)

int, instance of sklearn.cluster model, default 3 int, instance of sklearn.cluster model, default 3

int, int > 0 int, int > 0

int, nb_iter > 0 int, nb_iter > 0

int, nb_trials > 0 or 2-tuple int, nb_trials > 0 or 2-tuple

int, optional int, optional

int, optional (default 5) int, optional (default 5)

int, optional (default = 1) int, optional (default = 1)

int, optional (default = 30) int, optional (default = 30)

int, optional (default = 5) int, optional (default = 5)

int, optional (default = None) int, optional (default = None)

int, optional (default: 0) int, optional (default: 0)

int, optional (default: 100) int, optional (default: 100)

int, optional (default: 1000) int, optional (default: 1000)

int, optional (default: 2) int, optional (default: 2)

int, optional (default: 300) int, optional (default: 300)

int, optional (default: 5) int, optional (default: 5)

int, optional (default=-1) int, optional (default=-1)

int, optional (default=0) int, optional (default=0)

int, optional (default=1) int, optional (default=1)

int, optional (default=10) int, optional (default=10)

int, optional (default=100) int, optional (default=100)

int, optional (default=1000) int, optional (default=1000)

int, optional (default=12000) int, optional (default=12000)

int, optional (default=128) int, optional (default=128)

int, optional (default=1e5) int, optional (default=1e5)

int, optional (default=1e6) int, optional (default=1e6)

int, optional (default=2) int, optional (default=2)

int, optional (default=20) int, optional (default=20)

int, optional (default=3) int, optional (default=3)

int, optional (default=30) int, optional (default=30)

int, optional (default=5) int, optional (default=5)

int, optional (default=50) int, optional (default=50)

int, optional (default=None) int, optional (default=None)

int, optional, default 'auto' int, optional, default 'auto'

int, optional, default 1 int, optional, default 1

int, optional, default 10 int, optional, default 10

int, optional, default 1e4 int, optional, default 1e4

int, optional, default 200 int, optional, default 200

int, optional, default 300 int, optional, default 300

int, optional, default None int, optional, default None

int, optional, default: 0 int, optional, default: 0

int, optional, default: 1 int, optional, default: 1

int, optional, default: 10 int, optional, default: 10

int, optional, default: 100 int, optional, default: 100

int, optional, default: 15 int, optional, default: 15

int, optional, default: 2 int, optional, default: 2

int, optional, default: 200 int, optional, default: 200

int, optional, default: 3 * batch_size int, optional, default: 3 * batch_size

int, optional, default: 30 int, optional, default: 30

int, optional, default: 300 int, optional, default: 300

int, optional, default: 4 int, optional, default: 4

int, optional, default: 8 int, optional, default: 8

int, optional, default: None int, optional, default: None

int, optional, default=1 int, optional, default=1

int, optional, default=10 int, optional, default=10

int, optional, default=100 int, optional, default=100

int, optional, default=200 int, optional, default=200

int, or string, optional int, or string, optional

integer integer

integer > 0 integer > 0

integer ndarray with shape (n_samples,) integer ndarray with shape (n_samples,)

integer or "NaN", optional (default="NaN") integer or "NaN", optional (default="NaN")

integer or None, optional (default=None) integer or None, optional (default=None)

integer or cross-validation generator integer or cross-validation generator

integer or float, optional default is None integer or float, optional default is None

integer or iterable (n_row_clusters, n_column_clusters) integer or iterable (n_row_clusters, n_column_clusters)

integer or numpy.RandomState, optional integer or numpy.RandomState, optional

integer or string, optional integer or string, optional

integer or tuple (n_row_clusters, n_column_clusters) integer or tuple (n_row_clusters, n_column_clusters)

integer or tuple of length arr.ndim integer or tuple of length arr.ndim

integer, between 0 and 10, optional (default=10) integer, between 0 and 10, optional (default=10)

integer, cross-validation generator, iterable or "prefit", optional integer, cross-validation generator, iterable or "prefit", optional

integer, default 100 integer, default 100

integer, default: 0 integer, default: 0

integer, default: 200 integer, default: 200

integer, default=(2 ** 20) integer, default=(2 ** 20)

integer, optional integer, optional

integer, optional (default = 2) integer, optional (default = 2)

integer, optional (default=0) integer, optional (default=0)

integer, optional (default=1) integer, optional (default=1)

integer, optional (default=10) integer, optional (default=10)

integer, optional (default=2) integer, optional (default=2)

integer, optional (default=3) integer, optional (default=3)

integer, optional (default=5) integer, optional (default=5)

integer, optional (default=50) integer, optional (default=50)

integer, optional, default -1 integer, optional, default -1

integer, optional, default 0 integer, optional, default 0

integer, optional, default 1 integer, optional, default 1

integer, optional, default 8 integer, optional, default 8

integer, optional, default: 3 integer, optional, default: 3

integer, optional, default: 6 integer, optional, default: 6

integer, or list positive float, optional integer, or list positive float, optional

is not used: placeholder to allow for usage in a Pipeline. is not used: placeholder to allow for usage in a Pipeline.

iterable iterable

iterable (n_rows, n_cols) iterable (n_rows, n_cols)

iterable of floating-point values iterable of floating-point values

iterable of floating-point values, optional, default: None iterable of floating-point values, optional, default: None

iterable of iterables iterable of iterables

iterable or None, default None iterable or None, default None

iterable or array-like, depending on transformers iterable or array-like, depending on transformers

iterable over iterable over raw features, length = n_samples iterable over iterable over raw features, length = n_samples

iterable over raw text documents, length = n_samples iterable over raw text documents, length = n_samples

iterable over {str, file-like, int} iterable over {str, file-like, int}

iterable, default=None iterable, default=None

joblib.Parallel joblib.Parallel

joblib.Parallel (optional) joblib.Parallel (optional)

kernel object kernel object

list list

list (len() equal to cv or 1 if cv == "prefit") list (len() equal to cv or 1 if cv == "prefit")

list of (objective, dual_gap) pairs list of (objective, dual_gap) pairs

list of (string, estimator) tuples list of (string, estimator) tuples

list of (string, transformer) tuples list of (string, transformer) tuples

list of DecisionTreeClassifier list of DecisionTreeClassifier

list of DecisionTreeRegressor list of DecisionTreeRegressor

list of GaussianRandomProjectionHash objects list of GaussianRandomProjectionHash objects

list of n_output estimators list of n_output estimators

list of int(n_classes * code_size) estimators list of int(n_classes * code_size) estimators

list of n_classes * (n_classes - 1) / 2 estimators list of n_classes * (n_classes - 1) / 2 estimators

list of n_classes estimators list of n_classes estimators

list of array-like list of array-like

list of array-like, shape = [n_features, n_features] list of array-like, shape = [n_features, n_features]

list of arrays list of arrays

list of arrays, len = n_samples list of arrays, len = n_samples

list of classifiers list of classifiers

list of dict list of dict

list of dict_type objects, length = n_samples list of dict_type objects, length = n_samples

list of estimators list of estimators

list of float list of float

list of floating-point values list of floating-point values

list of floats or None (default=None) list of floats or None (default=None)

list of floats | int list of floats | int

list of indices list of indices

list of integers of size n_outputs list of integers of size n_outputs

list of named tuples list of named tuples

list of numpy arrays, shape (n_outputs) list of numpy arrays, shape (n_outputs)

list of positive floats list of positive floats

list of size n_outputs of arrays of size (n_classes,) list of size n_outputs of arrays of size (n_classes,)

list of string, length n_features, optional list of string, length n_features, optional

list of string, length n_output_features list of string, length n_output_features

list of strings list of strings

list of strings, bool or None, optional (default=None) list of strings, bool or None, optional (default=None)

list of strings, optional (default=None) list of strings, optional (default=None)

list of tuples list of tuples

list, [n_iterations] list, [n_iterations]

list, default None list, default None

list, length = 2 * len(arrays), list, length = 2 * len(arrays),

list, length = len(coefs_) + len(intercepts_) list, length = len(coefs_) + len(intercepts_)

list, length = len(grads) list, length = len(grads)

list, length = len(params) list, length = len(params)

list, length = n_alphas | list of n_targets such lists list, length = n_alphas | list of n_targets such lists

list, length = n_layers - 1 list, length = n_layers - 1

list, length n list, length n

list, length n_layers - 1 list, length n_layers - 1

list, length=2 * len(arrays) list, length=2 * len(arrays)

list, optional list, optional

list-like list-like

mapping of string to any mapping of string to any

mapping of string to any, default=None mapping of string to any, default=None

mapping of string to any, optional mapping of string to any, optional

maximum number of iterations for 'arpack' method maximum number of iterations for 'arpack' method

nd-array or sparse matrix nd-array or sparse matrix

nd-array, list or sparse matrix nd-array, list or sparse matrix

ndarray ndarray

ndarray (n_samples, ) ndarray (n_samples, )

ndarray (n_samples, n_features) ndarray (n_samples, n_features)

ndarray of DecisionTreeRegressor, shape = [n_estimators, 1] ndarray of DecisionTreeRegressor, shape = [n_estimators, 1]

ndarray of DecisionTreeRegressor, shape = [n_estimators, loss_.K] ndarray of DecisionTreeRegressor, shape = [n_estimators, loss_.K]

ndarray of booleans, optional ndarray of booleans, optional

ndarray of float ndarray of float

ndarray of int ndarray of int

ndarray of shape (n_samples,), or, in the multilabel a list of ndarray of shape (n_samples,), or, in the multilabel a list of

ndarray of shape (n_samples_1, n_features) ndarray of shape (n_samples_1, n_features)

ndarray of shape (n_samples_2, n_features) ndarray of shape (n_samples_2, n_features)

ndarray of shape(n) ndarray of shape(n)

ndarray of shape(p, n) ndarray of shape(p, n)

ndarray or csc_matrix, shape (n_samples, n_features) ndarray or csc_matrix, shape (n_samples, n_features)

ndarray or sparse array, shape: (n_samples_X, n_features) ndarray or sparse array, shape: (n_samples_X, n_features)

ndarray or sparse array, shape: (n_samples_Y, n_features) ndarray or sparse array, shape: (n_samples_Y, n_features)

ndarray or sparse matrix ndarray or sparse matrix

ndarray or sparse matrix, shape (n_samples, n_features) ndarray or sparse matrix, shape (n_samples, n_features)

ndarray with same shape as u ndarray with same shape as u

ndarray, ndarray,

ndarray, 2D or 3D ndarray, 2D or 3D

ndarray, dtype int or bool ndarray, dtype int or bool

ndarray, optional ndarray, optional

ndarray, shape () ndarray, shape ()

ndarray, shape (branching_factor + 1, n_features) ndarray, shape (branching_factor + 1, n_features)

ndarray, shape (branching_factor + 1,) ndarray, shape (branching_factor + 1,)

ndarray, shape (len(w)) ndarray, shape (len(w))

ndarray, shape (n_classes * n_features,) or ndarray, shape (n_classes * n_features,) or

ndarray, shape (n_classes, n_features) ndarray, shape (n_classes, n_features)

ndarray, shape (n_classes,) ndarray, shape (n_classes,)

ndarray, shape (n_cs, n_features) or (n_cs, n_features + 1) ndarray, shape (n_cs, n_features) or (n_cs, n_features + 1)

ndarray, shape (n_cs,) ndarray, shape (n_cs,)

ndarray, shape (n_features + 1,) or (n_features + 2,) ndarray, shape (n_features + 1,) or (n_features + 2,)

ndarray, shape (n_features, n_features + 1) ndarray, shape (n_features, n_features + 1)

ndarray, shape (n_features,) ndarray, shape (n_features,)

ndarray, shape (n_features,) or (n_features + 1,) ndarray, shape (n_features,) or (n_features + 1,)

ndarray, shape (n_features,), optional ndarray, shape (n_features,), optional

ndarray, shape (n_nodes-1,) ndarray, shape (n_nodes-1,)

ndarray, shape (n_quantiles, n_features) ndarray, shape (n_quantiles, n_features)

ndarray, shape (n_samples, ) ndarray, shape (n_samples, )

ndarray, shape (n_samples, n_classes) ndarray, shape (n_samples, n_classes)

ndarray, shape (n_samples, n_components) ndarray, shape (n_samples, n_components)

ndarray, shape (n_samples, n_components), optional, default: None ndarray, shape (n_samples, n_components), optional, default: None

ndarray, shape (n_samples, n_features) ndarray, shape (n_samples, n_features)

ndarray, shape (n_samples, n_samples) ndarray, shape (n_samples, n_samples)

ndarray, shape (n_samples,) ndarray, shape (n_samples,)

ndarray, shape (n_samples,) or (n_samples, n_outputs) ndarray, shape (n_samples,) or (n_samples, n_outputs)

ndarray, shape (n_samples,), optional ndarray, shape (n_samples,), optional

ndarray, shape (n_samples,), optional, default: None ndarray, shape (n_samples,), optional, default: None

ndarray, shape (n_samples,), or (n_samples, n_outputs) ndarray, shape (n_samples,), or (n_samples, n_outputs)

ndarray, shape(n_quantiles, ) ndarray, shape(n_quantiles, )

ndarray, shape(n_samples) ndarray, shape(n_samples)

ndarray, shape=(n, m) ndarray, shape=(n, m)

ndarray, shape=(n,) ndarray, shape=(n,)

node label node label

non-negative real non-negative real

non-negative real, default 1e-06 non-negative real, default 1e-06

non-negative real, default 1e-06. non-negative real, default 1e-06.

non-zero int, inf, -inf, default 1 non-zero int, inf, -inf, default 1

not used, present for API consistence purpose. not used, present for API consistence purpose.

np.array, dtype=np.intp np.array, dtype=np.intp

np.ndarray np.ndarray

np.ndarray or a sparse matrix class, optional np.ndarray or a sparse matrix class, optional

np.ndarray shape [n_samples, NP] np.ndarray shape [n_samples, NP]

number number

number type, default np.float64 number type, default np.float64

number type, default=np.float number type, default=np.float

numpy array of shape (2200, 2, 62, 47). Shape depends on numpy array of shape (2200, 2, 62, 47). Shape depends on

numpy array of shape (2200, 5828). Shape depends on subset. numpy array of shape (2200, 5828). Shape depends on subset.

numpy array of shape (2200,). Shape depends on subset. numpy array of shape (2200,). Shape depends on subset.

numpy array of shape (400, ) numpy array of shape (400, )

numpy array of shape (400, 4096) numpy array of shape (400, 4096)

numpy array of shape (400, 64, 64) numpy array of shape (400, 64, 64)

numpy array of shape (n_samples,) numpy array of shape (n_samples,)

numpy array of shape [n_alphas] numpy array of shape [n_alphas]

numpy array of shape [n_classes, code_size] numpy array of shape [n_classes, code_size]

numpy array of shape [n_classes] numpy array of shape [n_classes]

numpy array of shape [n_components, n_features] numpy array of shape [n_components, n_features]

numpy array of shape [n_samples, n_features] numpy array of shape [n_samples, n_features]

numpy array of shape [n_samples, n_features_new] numpy array of shape [n_samples, n_features_new]

numpy array of shape [n_samples, n_samples] numpy array of shape [n_samples, n_samples]

numpy array of shape [n_samples, n_targets] numpy array of shape [n_samples, n_targets]

numpy array of shape [n_samples,n_features] numpy array of shape [n_samples,n_features]

numpy array of shape [n_samples1, n_samples2] numpy array of shape [n_samples1, n_samples2]

numpy array of shape [n_samples] numpy array of shape [n_samples]

numpy array of shape [n_unique_labels] numpy array of shape [n_unique_labels]

numpy array or CSR matrix [n_components, n_features] numpy array or CSR matrix [n_components, n_features]

numpy array or CSR matrix of shape [n_samples, n_classes] numpy array or CSR matrix of shape [n_samples, n_classes]

numpy array or CSR matrix of shape [n_samples] Target values. numpy array or CSR matrix of shape [n_samples] Target values.

numpy array or scipy sparse of shape [n_samples, n_components] numpy array or scipy sparse of shape [n_samples, n_components]

numpy array or scipy.sparse matrix of shape (n_samples, n_features) numpy array or scipy.sparse matrix of shape (n_samples, n_features)

numpy array or scipy.sparse of shape [n_samples, n_features] numpy array or scipy.sparse of shape [n_samples, n_features]

numpy array or sparse matrix of shape [n_samples, n_features] numpy array or sparse matrix of shape [n_samples, n_features]

numpy array or sparse matrix of shape [n_samples,n_features] numpy array or sparse matrix of shape [n_samples,n_features]

numpy array or sparse matrix with shape [n_samples, n_classes] numpy array or sparse matrix with shape [n_samples, n_classes]

numpy array, dtype=np.int, shape (n_samples,) numpy array, dtype=np.int, shape (n_samples,)

numpy array, optional numpy array, optional

numpy array, shape (n_alphas,) numpy array, shape (n_alphas,)

numpy array, shape (n_alphas,) or (n_l1_ratio, n_alphas) numpy array, shape (n_alphas,) or (n_l1_ratio, n_alphas)

numpy array, shape (n_clusters, n_features) numpy array, shape (n_clusters, n_features)

numpy array, shape (n_clusters,) numpy array, shape (n_clusters,)

numpy array, shape (n_sample, n_features) numpy array, shape (n_sample, n_features)

numpy array, shape (n_samples,) numpy array, shape (n_samples,)

numpy data type, default np.float64 numpy data type, default np.float64

numpy random number generator or seed integer numpy random number generator or seed integer

numpy type, optional, default np.float64 numpy type, optional, default np.float64

numpy.RandomState numpy.RandomState

numpy.ndarray numpy.ndarray

numpy.ndarray, shape (n_features, n_features) numpy.ndarray, shape (n_features, n_features)

object object

object or None, optional (default=None) object or None, optional (default=None)

object type that implements the "fit" and "predict" methods object type that implements the "fit" and "predict" methods

object with the joblib.Memory interface object with the joblib.Memory interface

object, default=LinearRegression() object, default=LinearRegression()

object, default=None object, default=None

object, optional object, optional

object, optional (default=DecisionTreeClassifier) object, optional (default=DecisionTreeClassifier)

object, optional (default=DecisionTreeRegressor) object, optional (default=DecisionTreeRegressor)

object, optional (default=None) object, optional (default=None)

one of {'continuous', continuous-multioutput'} one of {'continuous', continuous-multioutput'}

one of {'multilabel-indicator', 'multiclass', 'binary'} one of {'multilabel-indicator', 'multiclass', 'binary'}

optional optional

optional, True by default optional, True by default

optional, default: 'data' optional, default: 'data'

optional, default: 'label' optional, default: 'label'

optional, default: 'train' optional, default: 'train'

optional, default: None optional, default: None

optional, default: True optional, default: True

optional, default=True optional, default=True

pair of floats (min, max), optional (default=(-10.0, 10.0)) pair of floats (min, max), optional (default=(-10.0, 10.0))

pair of floats >= 0, default: (1e-5, 1e5) pair of floats >= 0, default: (1e-5, 1e5)

positive float positive float

positive float, default 0.01 positive float, default 0.01

positive float, default 1e-4 positive float, default 1e-4

positive float, optional positive float, optional

property property

random state random state

record array, shape = (1623,) record array, shape = (1623,)

record array, shape = (619,) record array, shape = (619,)

returns a trained MLP model. returns a trained MLP model.

returns an instance of self. returns an instance of self.

returns this MultiLabelBinarizer instance returns this MultiLabelBinarizer instance

scipy sparse matrix scipy sparse matrix

scipy sparse matrix. scipy sparse matrix.

scipy.sparse matrix of shape (n_samples, n_features) scipy.sparse matrix of shape (n_samples, n_features)

scipy.sparse matrix, shape (n_features, 1) | (n_targets, n_features) scipy.sparse matrix, shape (n_features, 1) | (n_targets, n_features)

scipy.sparse matrix, shape = (n_samples, self.n_features) scipy.sparse matrix, shape = (n_samples, self.n_features)

scipy.sparse.csc_matrix, shape=(n_samples, n_features) scipy.sparse.csc_matrix, shape=(n_samples, n_features)

scipy.sparse.csr_matrix, shape=(n_samples, n_features) scipy.sparse.csr_matrix, shape=(n_samples, n_features)

select the portion to load: 'train', 'test' or 'raw' select the portion to load: 'train', 'test' or 'raw'

self self

seq of Axis objects seq of Axis objects

seq of ints, strings, or tuples of ints or strings seq of ints, strings, or tuples of ints or strings

seq of ndarray seq of ndarray

seq of ndarray or None seq of ndarray or None

seq of str seq of str

sequence sequence

sequence of indexable data-structures sequence of indexable data-structures

set set

shape=(n_samples, n_components) shape=(n_samples, n_components)

sklearn estimator instance sklearn estimator instance

sklearn.neighbors.NearestNeighbors instance sklearn.neighbors.NearestNeighbors instance

sparse CSR matrix, shape (n_samples, n_classes) sparse CSR matrix, shape (n_samples, n_classes)

sparse csc matrix of size (n_samples, n_outputs) sparse csc matrix of size (n_samples, n_outputs)

sparse csr array, shape = [n_samples, n_nodes] sparse csr array, shape = [n_samples, n_nodes]

sparse matrix (optional). sparse matrix (optional).

sparse matrix CSC, shape (n_samples, n_features) sparse matrix CSC, shape (n_samples, n_features)

sparse matrix if sparse=True else a 2-d array, dtype=int sparse matrix if sparse=True else a 2-d array, dtype=int

sparse matrix in CSR format, shape = [n_samples, n_samples] sparse matrix in CSR format, shape = [n_samples, n_samples]

sparse matrix in CSR format, shape = [n_samples, n_samples_fit] sparse matrix in CSR format, shape = [n_samples, n_samples_fit]

sparse matrix of shape (dim, dim) sparse matrix of shape (dim, dim)

sparse matrix or 2D array (preferably LIL matrix) sparse matrix or 2D array (preferably LIL matrix)

sparse matrix or a 2-d array sparse matrix or a 2-d array

sparse matrix, [n_samples, n_features] sparse matrix, [n_samples, n_features]

sparse matrix, shape=(n_samples, n_out) sparse matrix, shape=(n_samples, n_out)

str str

str or callable str or callable

str or callable, optional (default = 'uniform') str or callable, optional (default = 'uniform')

str or estimator instance (default=None) str or estimator instance (default=None)

str or int, 1 by default str or int, 1 by default

str | None str | None

str | callable str | callable

str, str,

str, 'error' or 'ignore' str, 'error' or 'ignore'

str, 'l1' or 'l2' str, 'l1' or 'l2'

str, 'l1' or 'l2', default: 'l2' str, 'l1' or 'l2', default: 'l2'

str, 'none', 'l2', 'l1', or 'elasticnet' str, 'none', 'l2', 'l1', or 'elasticnet'

str, 'onehot', 'onehot-dense' or 'ordinal' str, 'onehot', 'onehot-dense' or 'ordinal'

str, (default='box-cox') str, (default='box-cox')

str, default 'cyclic' str, default 'cyclic'

str, default: 'hinge' str, default: 'hinge'

str, default: 'squared_loss' str, default: 'squared_loss'

str, default="stratified" str, default="stratified"

str, defaults to 'dirichlet_process'. str, defaults to 'dirichlet_process'.

str, optional str, optional

str, optional (default: None) str, optional (default: None)

str, optional (default='uniform') str, optional (default='uniform')

str, {'hard', 'soft'} (default='hard') str, {'hard', 'soft'} (default='hard')

str, {'l1', 'l2'} str, {'l1', 'l2'}

str, {'logistic_regression', 'hinge', 'squared_hinge', str, {'logistic_regression', 'hinge', 'squared_hinge',

str, {'ovr', 'crammer_singer'} str, {'ovr', 'crammer_singer'}

str, {'ovr', 'multinomial'} str, {'ovr', 'multinomial'}

str, {'ovr', 'multinomial'}, default: 'ovr' str, {'ovr', 'multinomial'}, default: 'ovr'

strictly positive float, optional (default=0.1) strictly positive float, optional (default=0.1)

strictly positive float, optional, (default=0.1) strictly positive float, optional, (default=0.1)

strictly positive integer strictly positive integer

strided ndarray strided ndarray

string string

string ('standard', 'hessian', 'modified' or 'ltsa') string ('standard', 'hessian', 'modified' or 'ltsa')

string (default: 'barnes_hut') string (default: 'barnes_hut')

string ['auto'|'FW'|'D'] string ['auto'|'FW'|'D']

string ['auto'|'brute'|'kd_tree'|'ball_tree'] string ['auto'|'brute'|'kd_tree'|'ball_tree']

string ['auto'|'dense'|'arpack'], default='auto' string ['auto'|'dense'|'arpack'], default='auto'

string in ['raw_values', 'uniform_average', 'variance_weighted'] or array-like of shape (n_outputs) string in ['raw_values', 'uniform_average', 'variance_weighted'] or array-like of shape (n_outputs)

string in ['raw_values', 'uniform_average', 'variance_weighted'] or None or array-like of shape (n_outputs) string in ['raw_values', 'uniform_average', 'variance_weighted'] or None or array-like of shape (n_outputs)

string in ['raw_values', 'uniform_average'] string in ['raw_values', 'uniform_average']

string in ['raw_values', 'uniform_average'] or array-like of shape = (n_outputs) string in ['raw_values', 'uniform_average'] or array-like of shape = (n_outputs)

string or None (default is None) string or None (default is None)

string or callable string or callable

string or callable, default "euclidean" string or callable, default "euclidean"

string or callable, default 'euclidean' string or callable, default 'euclidean'

string or callable, default 'minkowski' string or callable, default 'minkowski'

string or callable, default: "euclidean" string or callable, default: "euclidean"

string or callable, default="linear" string or callable, default="linear"

string or callable, default="rbf" string or callable, default="rbf"

string or callable, optional string or callable, optional

string or callable, optional (default: "fmin_l_bfgs_b") string or callable, optional (default: "fmin_l_bfgs_b")

string or callable, optional, default: "euclidean". string or callable, optional, default: "euclidean".

string or file object string or file object

string or file-like in binary mode string or file-like in binary mode

string or float, optional string or float, optional

string or function, optional, default: "jaccard" string or function, optional, default: "jaccard"

string or function, optional. Default: 'logcosh' string or function, optional. Default: 'logcosh'

string or numpy array, optional (default: "random") string or numpy array, optional (default: "random")

string or unicode string or unicode

string or unicode, optional (default=None) string or unicode, optional (default=None)

string {'auto', 'full', 'arpack', 'randomized'} string {'auto', 'full', 'arpack', 'randomized'}

string {'english'}, list, or None (default) string {'english'}, list, or None (default)

string {'filename', 'file', 'content'} string {'filename', 'file', 'content'}

string, "nipals" or "svd" string, "nipals" or "svd"

string, 'epsilon_insensitive' or 'squared_epsilon_insensitive' (default='epsilon_insensitive') string, 'epsilon_insensitive' or 'squared_epsilon_insensitive' (default='epsilon_insensitive')

string, 'hinge' or 'squared_hinge' (default='squared_hinge') string, 'hinge' or 'squared_hinge' (default='squared_hinge')

string, 'l1' or 'l2' (default='l2') string, 'l1' or 'l2' (default='l2')

string, 'ovr' or 'crammer_singer' (default='ovr') string, 'ovr' or 'crammer_singer' (default='ovr')

string, 'train', 'test', or 'all', default='all' string, 'train', 'test', or 'all', default='all'

string, 'utf-8' by default. string, 'utf-8' by default.

string, [None (default), 'binary', 'micro', 'macro', 'samples', 'weighted'] string, [None (default), 'binary', 'micro', 'macro', 'samples', 'weighted']

string, [None, 'binary' (default), 'micro', 'macro', 'samples', 'weighted'] string, [None, 'binary' (default), 'micro', 'macro', 'samples', 'weighted']

string, [None, 'micro', 'macro' (default), 'samples', 'weighted'] string, [None, 'micro', 'macro' (default), 'samples', 'weighted']

string, boolean or list of string (default=False) string, boolean or list of string (default=False)

string, boolean or list/tuple of strings string, boolean or list/tuple of strings

string, boolean or list/tuple of strings (default=False) string, boolean or list/tuple of strings (default=False)

string, callable or None, default=None string, callable or None, default=None

string, callable or None, optional, default: None string, callable or None, optional, default: None

string, callable, list/tuple, dict or None, default: None string, callable, list/tuple, dict or None, default: None

string, callable, optional, default "absolute_loss" string, callable, optional, default "absolute_loss"

string, callable, or None string, callable, or None

string, default 'diag' string, default 'diag'

string, default 'minkowski' string, default 'minkowski'

string, default 'wmc' string, default 'wmc'

string, default : "one_vs_rest" string, default : "one_vs_rest"

string, default = "randomized" string, default = "randomized"

string, default='' string, default=''

string, default='utf-8' string, default='utf-8'

string, float, optional default None string, float, optional default None

string, in {"log", "squared"} string, in {"log", "squared"}

string, list of string, or None, default=None string, list of string, or None, default=None

string, list of strings or tuple of strings string, list of strings or tuple of strings

string, optional string, optional

string, optional (default: None) string, optional (default: None)

string, optional (default="best") string, optional (default="best")

string, optional (default="friedman_mse") string, optional (default="friedman_mse")

string, optional (default="gini") string, optional (default="gini")

string, optional (default="mean") string, optional (default="mean")

string, optional (default="mse") string, optional (default="mse")

string, optional (default='rbf') string, optional (default='rbf')

string, optional, default "dict" string, optional, default "dict"

string, optional, default: "nan" string, optional, default: "nan"

string, optional, default: 'bistochastic' string, optional, default: 'bistochastic'

string, optional, default: 'predict' string, optional, default: 'predict'

string, optional, default: 'randomized' string, optional, default: 'randomized'

string, optional, default=``euclidean`` string, optional, default=``euclidean``

string, or callable string, or callable

string, or callable, default: "linear" string, or callable, default: "linear"

string, type or None string, type or None

string, type, list of types or None (default="numeric") string, type, list of types or None (default="numeric")

string, type, list of types or None (default=None) string, type, list of types or None (default=None)

string, {'auto', 'arpack', 'dense'} string, {'auto', 'arpack', 'dense'}

string, {'word', 'char', 'char_wb'} or callable string, {'word', 'char', 'char_wb'} or callable

string, {'word', 'char'} or callable string, {'word', 'char'} or callable

the filesystem path to the root folder where MLComp datasets the filesystem path to the root folder where MLComp datasets

the integer id or the string name metadata of the MLComp the integer id or the string name metadata of the MLComp

the return value of func the return value of func

the warning class the warning class

tree.Tree tree.Tree

tuple tuple

tuple (min, max), default=(0, 1) tuple (min, max), default=(0, 1)

tuple (min_n, max_n) tuple (min_n, max_n)

tuple (min_n, max_n), default=(1, 1) tuple (min_n, max_n), default=(1, 1)

tuple (q_min, q_max), 0.0 < q_min < q_max < 100.0 tuple (q_min, q_max), 0.0 < q_min < q_max < 100.0

tuple of (A, B) ndarrays tuple of (A, B) ndarrays

tuple of floats tuple of floats

tuple of ints (image_height, image_width) or tuple of ints (image_height, image_width) or

tuple of ints (patch_height, patch_width) tuple of ints (patch_height, patch_width)

tuple of warning class, default to Warning tuple of warning class, default to Warning

tuple or float tuple or float

tuple or set, for internal use tuple or set, for internal use

tuple, length = n_layers - 2, default (100,) tuple, length = n_layers - 2, default (100,)

tuple, optional tuple, optional

type, optional type, optional

warning class, defaults to Warning. warning class, defaults to Warning.

{"average", "complete"}, optional, default: "complete" {"average", "complete"}, optional, default: "complete"

{"ward", "complete", "average"}, optional, default "ward" {"ward", "complete", "average"}, optional, default "ward"

{"ward", "complete", "average"}, optional, default: "ward" {"ward", "complete", "average"}, optional, default: "ward"

{'F', 'C', or None}, optional {'F', 'C', or None}, optional

{'SAMME', 'SAMME.R'}, optional (default='SAMME.R') {'SAMME', 'SAMME.R'}, optional (default='SAMME.R')

{'all', 'root', 'none'}, optional (default='all') {'all', 'root', 'none'}, optional (default='all')

{'ascii', 'unicode', None} {'ascii', 'unicode', None}

{'auto', 'ball_tree', 'kd_tree', 'brute'}, optional {'auto', 'ball_tree', 'kd_tree', 'brute'}, optional

{'auto', 'svd', 'cholesky', 'lsqr', 'sparse_cg', 'sag', 'saga'} {'auto', 'svd', 'cholesky', 'lsqr', 'sparse_cg', 'sag', 'saga'}

{'auto', True, False} {'auto', True, False}

{'auto', bool, array_like}, default 'auto' {'auto', bool, array_like}, default 'auto'

{'cd', 'lars'} {'cd', 'lars'}

{'cd', 'lars'}, default 'cd' {'cd', 'lars'}, default 'cd'

{'connectivity', 'distance'}, optional {'connectivity', 'distance'}, optional

{'constant', 'adaptive', 'invscaling'}, default 'constant' {'constant', 'adaptive', 'invscaling'}, default 'constant'

{'constant', 'invscaling', 'adaptive'}, default 'constant' {'constant', 'invscaling', 'adaptive'}, default 'constant'

{'deviance', 'exponential'}, optional (default='deviance') {'deviance', 'exponential'}, optional (default='deviance')

{'full', 'tied', 'diag', 'spherical'} {'full', 'tied', 'diag', 'spherical'}

{'full', 'tied', 'diag', 'spherical'}, {'full', 'tied', 'diag', 'spherical'},

{'full', 'tied', 'diag', 'spherical'}, defaults to 'full' {'full', 'tied', 'diag', 'spherical'}, defaults to 'full'

{'identity', 'logistic', 'tanh', 'relu'}, default 'relu' {'identity', 'logistic', 'tanh', 'relu'}, default 'relu'

{'k-means++', 'random' or an ndarray} {'k-means++', 'random' or an ndarray}

{'k-means++', 'random' or an ndarray}, default: 'k-means++' {'k-means++', 'random' or an ndarray}, default: 'k-means++'

{'k-means++', 'random' or ndarray or callable} optional {'k-means++', 'random' or ndarray or callable} optional

{'k-means++', 'random', or ndarray, or a callable}, optional {'k-means++', 'random', or ndarray, or a callable}, optional

{'kmeans', 'random'}, defaults to 'kmeans'. {'kmeans', 'random'}, defaults to 'kmeans'.

{'knn', 'rbf', callable} {'knn', 'rbf', callable}

{'lapack', 'randomized'} {'lapack', 'randomized'}

{'lars', 'cd'} {'lars', 'cd'}

{'lasso_lars', 'lasso_cd', 'lars', 'omp', 'threshold'} {'lasso_lars', 'lasso_cd', 'lars', 'omp', 'threshold'}

{'lasso_lars', 'lasso_cd', 'lars', 'omp', 'threshold'} {'lasso_lars', 'lasso_cd', 'lars', 'omp', 'threshold'}

{'lbfgs', 'newton-cg', 'liblinear', 'sag', 'saga'} {'lbfgs', 'newton-cg', 'liblinear', 'sag', 'saga'}

{'lbfgs', 'sgd', 'adam'}, default 'adam' {'lbfgs', 'sgd', 'adam'}, default 'adam'

{'linear', 'square', 'exponential'}, optional (default='linear') {'linear', 'square', 'exponential'}, optional (default='linear')

{'ls', 'lad', 'huber', 'quantile'}, optional (default='ls') {'ls', 'lad', 'huber', 'quantile'}, optional (default='ls')

{'newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga'}, {'newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga'},

{'parallel', 'deflation'} {'parallel', 'deflation'}

{'parallel', 'deflation'}, optional {'parallel', 'deflation'}, optional

{'percentile', 'k_best', 'fpr', 'fdr', 'fwe'} {'percentile', 'k_best', 'fpr', 'fdr', 'fwe'}

{'squared_hinge', 'log'}, default 'squared_hinge' {'squared_hinge', 'log'}, default 'squared_hinge'

{'standard', 'hessian', 'modified', 'ltsa'} {'standard', 'hessian', 'modified', 'ltsa'}

{'strict', 'ignore', 'replace'} {'strict', 'ignore', 'replace'}

{'strict', 'ignore', 'replace'}, optional {'strict', 'ignore', 'replace'}, optional

{None, 'arpack', 'lobpcg', or 'amg'}, default None {None, 'arpack', 'lobpcg', or 'amg'}, default None

{None, 'auto', 'svd', eigen'}, optional {None, 'auto', 'svd', eigen'}, optional

{None, array, sparse matrix}, {None, array, sparse matrix},

{True, False, 'auto'}, {True, False, 'auto'},

{True, False, 'auto'}, default 'auto' {True, False, 'auto'}, default 'auto'

{array, matrix, sparse matrix, LinearOperator} {array, matrix, sparse matrix, LinearOperator}

{array, sparse matrix} {array, sparse matrix}

{array, sparse matrix}, shape = (n_samples, n_features * (2*sample_steps + 1)) {array, sparse matrix}, shape = (n_samples, n_features * (2*sample_steps + 1))

{array, sparse matrix}, shape (n_samples_1, n_samples_2) {array, sparse matrix}, shape (n_samples_1, n_samples_2)

{array, sparse matrix}, shape = [n_samples, n_features] {array, sparse matrix}, shape = [n_samples, n_features]

{array, sparse matrix}, shape [n_samples, n_features + 1] {array, sparse matrix}, shape [n_samples, n_features + 1]

{array-like, object with finite length or shape} {array-like, object with finite length or shape}

{array-like, sparse matrix, BallTree, KDTree, NearestNeighbors} {array-like, sparse matrix, BallTree, KDTree, NearestNeighbors}

{array-like, sparse matrix, BallTree, KDTree} {array-like, sparse matrix, BallTree, KDTree}

{array-like, sparse matrix, LinearOperator}, {array-like, sparse matrix, LinearOperator},

{array-like, sparse matrix} {array-like, sparse matrix}

{array-like, sparse matrix} shape = (n_samples, n_features) {array-like, sparse matrix} shape = (n_samples, n_features)

{array-like, sparse matrix} of shape = [n_samples, n_features] {array-like, sparse matrix} of shape = [n_samples, n_features]

{array-like, sparse matrix} shape (n_samples, n_features) {array-like, sparse matrix} shape (n_samples, n_features)

{array-like, sparse matrix} shape = [n_samples, n_features] {array-like, sparse matrix} shape = [n_samples, n_features]

{array-like, sparse matrix}, shape (n_samples, n_clusters) {array-like, sparse matrix}, shape (n_samples, n_clusters)

{array-like, sparse matrix}, shape (n_samples, n_components) {array-like, sparse matrix}, shape (n_samples, n_components)

{array-like, sparse matrix}, shape (n_samples, n_features) {array-like, sparse matrix}, shape (n_samples, n_features)

{array-like, sparse matrix}, shape (n_samples, n_features), None {array-like, sparse matrix}, shape (n_samples, n_features), None

{array-like, sparse matrix}, shape (n_samples1, n_features) {array-like, sparse matrix}, shape (n_samples1, n_features)

{array-like, sparse matrix}, shape (n_samples2, n_features) {array-like, sparse matrix}, shape (n_samples2, n_features)

{array-like, sparse matrix}, shape (n_samples_1, n_features) {array-like, sparse matrix}, shape (n_samples_1, n_features)

{array-like, sparse matrix}, shape (n_samples_2, n_features) {array-like, sparse matrix}, shape (n_samples_2, n_features)

{array-like, sparse matrix}, shape (n_samples_a, n_features) {array-like, sparse matrix}, shape (n_samples_a, n_features)

{array-like, sparse matrix}, shape (n_samples_b, n_features) {array-like, sparse matrix}, shape (n_samples_b, n_features)

{array-like, sparse matrix}, shape = (n_samples, n_features) {array-like, sparse matrix}, shape = (n_samples, n_features)

{array-like, sparse matrix}, shape = (n_samples, n_features_in) {array-like, sparse matrix}, shape = (n_samples, n_features_in)

{array-like, sparse matrix}, shape = [n_samples (, n_labels)] {array-like, sparse matrix}, shape = [n_samples (, n_labels)]

{array-like, sparse matrix}, shape = [n_samples, n_features] {array-like, sparse matrix}, shape = [n_samples, n_features]

{array-like, sparse matrix}, shape = [n_samples,n_features] {array-like, sparse matrix}, shape = [n_samples,n_features]

{array-like, sparse matrix}, shape [n_samples, n_features] {array-like, sparse matrix}, shape [n_samples, n_features]

{array-like, sparse matrix}, shape=[n_samples, n_features] {array-like, sparse matrix}, shape=[n_samples, n_features]

{array-like, sparse}, shape=[n_classes_true, n_classes_pred] {array-like, sparse}, shape=[n_classes_true, n_classes_pred]

{array-like}, shape (n_samples, n_features) {array-like}, shape (n_samples, n_features)

{dict, 'balanced'}, optional {dict, 'balanced'}, optional

{float, array-like}, {float, array-like},

{float, array-like}, shape (n_targets) {float, array-like}, shape (n_targets)

{float, array-like}, shape = [n_targets] {float, array-like}, shape = [n_targets]

{sparse matrix, ndarray, LinearOperatorLinear} {sparse matrix, ndarray, LinearOperatorLinear}

{str, file-like, int} {str, file-like, int}