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)
