Source code for skmultilearn.cluster.matrix

from __future__ import absolute_import
from builtins import range
from .base import LabelSpaceClustererBase
import numpy as np

[docs]class MatrixLabelSpaceClusterer(LabelSpaceClustererBase): """Clusters the label space using a matrix-based clusterer :param clusterer: a clonable instance of a `scikit-compatible matrix-based <>`_ clusterer :param pass_input_space bool: whether to take ``X`` into consideration upon clustering, use only if you know that the clusterer can handle two parameters for clustering """ def __init__(self, clusterer=None, pass_input_space=False): super(MatrixLabelSpaceClusterer, self).__init__() self.clusterer = clusterer self.pass_input_space = pass_input_space
[docs] def fit_predict(self, X, y): """ Cluster the output space Uses the ``fit_predict`` method of provided ``clusterer`` to perform label space division. :returns: partition of labels, each sublist contains label indices related to label positions in ``y`` :rtype: nd.array of nd.arrays :returns: this is just an abstract method """ if self.pass_input_space: return self.clusterer.fit_predict(X, y.transpose()) return self.clusterer.fit_predict(y.transpose())