def test_foreshadow_serialization_boston_housing_regression_multiprocessing( tmpdir): from foreshadow.foreshadow import Foreshadow import pandas as pd import numpy as np from sklearn.datasets import load_boston from sklearn.model_selection import train_test_split from sklearn.linear_model import LinearRegression np.random.seed(1337) boston = load_boston() X_df = pd.DataFrame(boston.data, columns=boston.feature_names) y_df = pd.DataFrame(boston.target, columns=["target"]) X_train, X_test, y_train, y_test = train_test_split(X_df, y_df, test_size=0.2) shadow = Foreshadow(estimator=LinearRegression(), problem_type=ProblemType.REGRESSION) shadow.configure_multiprocessing(n_job=-1) shadow.fit(X_train, y_train) score = shadow.score(X_test, y_test) print(score)