def test_ridge_regression_model_default(datatype):
X_train, X_test, y_train, y_test = small_regression_dataset(datatype)
curidge = cuRidge()
# fit and predict cuml ridge regression model
curidge.fit(X_train, y_train)
curidge_predict = curidge.predict(X_test)
# sklearn ridge regression model initialization, fit and predict
skridge = skRidge()
skridge.fit(X_train, y_train)
skridge_predict = skridge.predict(X_test)
assert array_equal(skridge_predict, curidge_predict, 1e-1, with_sign=True)
def test_linear_regression_model_default(datatype):
X_train, X_test, y_train, y_test = small_regression_dataset(datatype)
# Initialization of cuML's linear regression model
cuols = cuLinearRegression()
# fit and predict cuml linear regression model
cuols.fit(X_train, y_train)
cuols_predict = cuols.predict(X_test)
# sklearn linear regression model initialization and fit
skols = skLinearRegression()
skols.fit(X_train, y_train)
skols_predict = skols.predict(X_test)
assert array_equal(skols_predict, cuols_predict, 1e-1, with_sign=True)
