def _calculate_information_gain(self, y, y1, y2):
# Calculate information gain
p = len(y1) / len(y)
entropy = calculate_entropy(y)
info_gain = entropy - p * calculate_entropy(y1) - (1 - p) * calculate_entropy(y2)
return info_gain
def _calculate_information_gain(self, y, y1, y2):
# Calculate information gain
p = len(y1) / len(y)
entropy = calculate_entropy(y)
info_gain = entropy - p * \
calculate_entropy(y1) - (1 - p) * \
calculate_entropy(y2)
return info_gain
def _calculate_information_gain(self, y, y1, y2):
with pyRAPL.Measurement('Information_gain', output=csv_output):
# Calculate information gain
p = len(y1) / len(y)
entropy = calculate_entropy(y)
info_gain = entropy - p * \
calculate_entropy(y1) - (1 - p) * \
calculate_entropy(y2)
return info_gain
csv_output.save()