sklearn.datasets.make_biclusters¶
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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.
See also
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.
