sklearn.datasets.make_sparse_coded_signal

sklearn.datasets.make_sparse_coded_signal(n_samples, *, n_components, n_features, n_nonzero_coefs, random_state=None) [source]

Generate a signal as a sparse combination of dictionary elements.

Returns a matrix Y = DX, such as D is (n_features, n_components), X is (n_components, n_samples) and each column of X has exactly n_nonzero_coefs non-zero elements.

Read more in the User Guide.

Parameters

n_samplesint

Number of samples to generate

n_componentsint

Number of components in the dictionary

n_featuresint

Number of features of the dataset to generate

n_nonzero_coefsint

Number of active (non-zero) coefficients in each sample

random_stateint, RandomState instance or None, default=None

Determines random number generation for dataset creation. Pass an int for reproducible output across multiple function calls. See Glossary.

Returns

datandarray of shape (n_features, n_samples)

The encoded signal (Y).

dictionaryndarray of shape (n_features, n_components)

The dictionary with normalized components (D).

codendarray of shape (n_components, n_samples)

The sparse code such that each column of this matrix has exactly n_nonzero_coefs non-zero items (X).

Examples using sklearn.datasets.make_sparse_coded_signal