jnothman

from sklearn.base import BaseEstimator, Clone
from sklearn.utils import safe_mask
class ModelByCluster(BaseEstimator):
    def __init__(self, clusterer, estimator):
        self.clusterer = clusterer
        self.estimator = estimator
    def fit(self, X, y):
        self.clusterer_ = clone(self.clusterer)
        clusters = self.clusterer_.fit_predict(X)
        n_clusters = len(np.unique(clusters))

naught101

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

These computations rely on nearest-neighbor statistics
'''
import numpy as np