Files changed (2)
-Currently supported techniques: clustering trees, PLS, binary relevance, chain classification and neural networks (for multi-label data only).
trees, based on the :obj:`SimpleTreeLearner`. It is implemented in C++ for speed and low memory usage.
-Features are selected by finding the furthest apart clusters measured with the euclidean distance between prototypes,
+Clustering trees work by splitting the data into clusters based on attributes. The attribute provides the optimal split based on a measure,
+the default used in this implementation is the Euclidean distance between the centroids of clusters, which we try to maximize.