sklearn.datasets.make_biclusters — scikit-learn 0.20.4 documentation (original) (raw)
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. |
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| 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. |
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