aab2ef03ff533c1160742fafd2bf12133e227ddb,nonconformist/ensemble.py,AggregatedCp,predict,#AggregatedCp#Any#Any#,41

Before Change

				if p_values is None:
					p_values = predictor.predict(x)
				else:
					p_values = np.dstack([p_values, predictor.predict(x)])

			p_values = self.p_agg_func(p_values)

			if significance:

After Change

	def predict(self, x, significance=None):
		is_regression = self.cp_class.problem_type == "regression"

		if is_regression:
			predictions = np.dstack([predictor.predict(x, significance) for
			                         predictor in self.predictors])
		else:
			predictions = np.dstack([predictor.predict(x) for
			                         predictor in self.predictors])

		predictions = self.p_agg_func(predictions)

		if significance and not is_regression:
			return predictions >= significance

Instances