sklearn.datasets.make_biclusters(shape, n_clusters, *, noise=0.0, minval=10, maxval=100, shuffle=True, random_state=None)[source]

Generate an array with constant block diagonal structure for biclustering.

Read more in the User Guide.

shapeiterable (n_rows, n_cols)

The shape of the result.


The number of biclusters.

noisefloat, optional (default=0.0)

The standard deviation of the gaussian noise.

minvalint, optional (default=10)

Minimum value of a bicluster.

maxvalint, optional (default=100)

Maximum value of a bicluster.

shuffleboolean, optional (default=True)

Shuffle the samples.

random_stateint, RandomState instance, default=None

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

Xarray of shape shape

The generated array.

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

The indicators for cluster membership of each row.

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

The indicators for cluster membership of each column.



Dhillon, I. S. (2001, August). Co-clustering documents and words using bipartite spectral graph partitioning. In Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 269-274). ACM.

Examples using sklearn.datasets.make_biclusters