Exemplo n.º 1
0
def test_one_doc_feature_importance():
    pool = Pool(TRAIN_FILE, column_description=CD_FILE)
    model = CatBoostClassifier(iterations=5, random_seed=0)
    model.fit(pool)
    np.save(
        FIMP_PATH,
        np.array(
            model.get_feature_importance(
                np.ones(pool.num_col(), dtype=int),
                0,
                cat_features=pool.get_cat_feature_indices(),
                fstr_type='Doc')))
    return local_canonical_file(FIMP_PATH)
Exemplo n.º 2
0
def test_one_doc_feature_importance():
    pool = Pool(TRAIN_FILE, column_description=CD_FILE)
    model = CatBoostClassifier(iterations=5, random_seed=0)
    model.fit(pool)
    np.save(FIMP_PATH, np.array(model.get_feature_importance(np.ones(pool.num_col(), dtype=int), 0, cat_features=pool.get_cat_feature_indices(), fstr_type='Doc')))
    return local_canonical_file(FIMP_PATH)