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:
				return p_values >= significance
			else:
				return p_values

		if self.cp_class.problem_type == "regression":
			intervals = None
			for predictor in self.predictors:

After Change

			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
		else:
			return predictions

Instances