How to use the suod.utils.utility.get_estimators function in suod

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github yzhao062 / SUOD / examples / demo_full.py View on Github external
mat = sp.io.loadmat(os.path.join('', 'datasets', mat_file))

    X = mat['X']
    y = mat['y']

    # split dataset into train and test
    X_train, X_test, y_train, y_test = \
        train_test_split(X, y, test_size=0.4, random_state=42)

    # standardize data to be digestible for most algorithms
    X_train, X_test = standardizer(X_train, X_test)

    contamination = y.sum() / len(y)

    # get estimators for training and prediction
    base_estimators = get_estimators(contamination=contamination)

    ##########################################################################
    model = SUOD(base_estimators=base_estimators, rp_flag_global=True,
                 approx_clf=approx_clf,
                 n_jobs=n_jobs, bps_flag=True, contamination=contamination,
                 approx_flag_global=True)

    start = time.time()
    model.fit(X_train)  # fit all models with X
    print('Fit time:', time.time() - start)
    print()

    start = time.time()
    model.approximate(X_train)  # conduct model approximation if it is enabled
    print('Approximation time:', time.time() - start)
    print()