sklearn.datasets.make_biclusters

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.

Parameters:
shape : iterable (n_rows, n_cols)

The shape of the result.

n_clusters : integer

The number of biclusters.

noise : float, optional (default=0.0)

The standard deviation of the gaussian noise.

minval : int, optional (default=10)

Minimum value of a bicluster.

maxval : int, optional (default=100)

Maximum value of a bicluster.

shuffle : boolean, optional (default=True)

Shuffle the samples.

random_state : int, RandomState instance or None (default)

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

Returns:
X : array of shape shape

The generated array.

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

The indicators for cluster membership of each row.

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

The indicators for cluster membership of each column.

References

[1]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