def _loadClassifier(self):
# Choose estimator
estimator = ELEProbDist
# Create the P(label) distribution
label_probdist = estimator(self._label_freqdist)
# Create the P(fval|label, fname) distribution
feature_probdist = {}
for ((label, fname), freqdist) in self._feature_freqdist.items():
probdist = estimator(freqdist, bins=len(self._feature_values[fname]))
feature_probdist[label,fname] = probdist
self._classifier = NaiveBayesClassifier(label_probdist, feature_probdist)
