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scikit-learn 1.3.2
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# `sklearn.datasets`.make_checkerboard

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

  Generate an array with block checkerboard structure for biclustering.

  Read more in the User Guide.

  Parameters:
    shape tuple of shape (n_rows, n_cols)

      The shape of the result.

    n_clusters int or array-like or shape (n_row_clusters, n_column_clusters)

      The number of row and column clusters.

    noise float, default=0.0

      The standard deviation of the gaussian noise.

    minval float, default=10

      Minimum value of a bicluster.

    maxval float, default=100

      Maximum value of a bicluster.

    shuffle bool, default=True

      Shuffle the samples.

    random_state int, 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:
    X ndarray of shape `shape`

      The generated array.

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

      The indicators for cluster membership of each row.

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

      The indicators for cluster membership of each column.

  See also

  `make_biclusters`

    Generate an array with constant block diagonal structure for biclustering.

  References

  [1]

  Kluger, Y., Basri, R., Chang, J. T., & Gerstein, M. (2003). Spectral biclustering of microarray data: coclustering genes and conditions. Genome research, 13(4), 703-716.

## Examples using `sklearn.datasets.make_checkerboard`

A demo of the Spectral Biclustering algorithm

A demo of the Spectral Biclustering algorithm