b70e10b94af7c7e4c4ed88e6516134580c389a34,libact/query_strategies/variance_reduction.py,VarianceReduction,make_query,#VarianceReduction#Any#Any#Any#,82

Before Change

        clf = copy.copy(self.model)
        clf.train(Dataset(Xlabeled, y))

        errors = Parallel(n_jobs=n_jobs)(delayed(self.E)(Xlabeled, y, x, clf,
            label_count) for x in X_pool)

        return unlabeled_entry_ids[errors.index(min(errors))]

After Change

        //errors = []
        //for x in X_pool:
        //    errors.append(self.E((Xlabeled, y, x, clf, label_count)))
        errors = p.map(self.E, [(Xlabeled, y, x, clf, label_count) for x in\
            X_pool])
        //print(errors)
        end = time.time()

Instances