def METHOD_NAME(self):
    X, y = load_iris(return_X_y=True)
    n_classes = 3
    clf = LogisticRegression(fit_intercept=False, max_iter=1000, random_state=0).fit(
        X, y
    )
    builder = d4p.logistic_regression_model_builder(
        n_classes=n_classes, n_features=X.shape[1]
    )
    builder.set_beta(clf.coef_, clf.intercept_)
    alg_pred = d4p.logistic_regression_prediction(nClasses=n_classes)
    pred_daal = alg_pred.compute(X, builder.model).prediction.flatten()
    pred_sklearn = clf.predict(X)
    self.assertTrue(np.allclose(pred_daal, pred_sklearn))