BiclusterMixin#
- class sklearn.base.BiclusterMixin[source]#
Mixin class for all bicluster estimators in scikit-learn.
This mixin defines the following functionality:
biclusters_
property that returns the row and column indicators;get_indices
method that returns the row and column indices of a bicluster;get_shape
method that returns the shape of a bicluster;get_submatrix
method that returns the submatrix corresponding to a bicluster.
Examples
>>> import numpy as np >>> from sklearn.base import BaseEstimator, BiclusterMixin >>> class DummyBiClustering(BiclusterMixin, BaseEstimator): ... def fit(self, X, y=None): ... self.rows_ = np.ones(shape=(1, X.shape[0]), dtype=bool) ... self.columns_ = np.ones(shape=(1, X.shape[1]), dtype=bool) ... return self >>> X = np.array([[1, 1], [2, 1], [1, 0], ... [4, 7], [3, 5], [3, 6]]) >>> bicluster = DummyBiClustering().fit(X) >>> hasattr(bicluster, "biclusters_") True >>> bicluster.get_indices(0) (array([0, 1, 2, 3, 4, 5]), array([0, 1]))
- property biclusters_#
Convenient way to get row and column indicators together.
Returns the
rows_
andcolumns_
members.
- get_indices(i)[source]#
Row and column indices of the
i
’th bicluster.Only works if
rows_
andcolumns_
attributes exist.- Parameters:
- iint
The index of the cluster.
- Returns:
- row_indndarray, dtype=np.intp
Indices of rows in the dataset that belong to the bicluster.
- col_indndarray, dtype=np.intp
Indices of columns in the dataset that belong to the bicluster.
- get_shape(i)[source]#
Shape of the
i
’th bicluster.- Parameters:
- iint
The index of the cluster.
- Returns:
- n_rowsint
Number of rows in the bicluster.
- n_colsint
Number of columns in the bicluster.
- get_submatrix(i, data)[source]#
Return the submatrix corresponding to bicluster
i
.- Parameters:
- iint
The index of the cluster.
- dataarray-like of shape (n_samples, n_features)
The data.
- Returns:
- submatrixndarray of shape (n_rows, n_cols)
The submatrix corresponding to bicluster
i
.
Notes
Works with sparse matrices. Only works if
rows_
andcolumns_
attributes exist.