def compute_info_gain(df, feature, split, y):
A = df[[feature, y]]
# series = [split for x in range(0, len(A[feature]))]
# print series
mask = A[feature] <= split
B = A[mask]
C = A[~mask]
info_gain = mystats.binary_entropy(A, y) - mystats.binary_entropy(B, y) + mystats.binary_entropy(C, y)
# print 'Information Gain: %s' % info_gain
return info_gain
