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)