Ensure that ReliefF with % neighbors works in a sklearn pipeline when it is parallelized
np.random.seed(49082)
clf = make_pipeline(ReliefF(n_features_to_select=2, n_neighbors=0.1, n_jobs=-1),
RandomForestClassifier(n_estimators=100, n_jobs=-1))
assert np.mean(cross_val_score(clf, features, labels, cv=3)) > 0.7
After Change
Check: Data (Binary Endpoint, Discrete Features): ReliefF with % neighbors works in a sklearn pipeline
np.random.seed(49082)
clf = make_pipeline(ReliefF(n_features_to_select=2, n_neighbors=0.1),
RandomForestClassifier(n_estimators=100, n_jobs=-1))
assert np.mean(cross_val_score(clf, features, labels, cv=3, n_jobs=-1)) > 0.7
