def METHOD_NAME():
    n_paa_segments = 10
    n_sax_symbols_avg = 8
    n_sax_symbols_slope = 8
    one_d_sax = OneD_SymbolicAggregateApproximation(
        n_segments=n_paa_segments,
        alphabet_size_avg=n_sax_symbols_avg,
        alphabet_size_slope=n_sax_symbols_slope)
    _check_not_fitted(one_d_sax)
    X = _get_random_walk()
    one_d_sax.fit(X)
    _check_params_predict(one_d_sax, X, ['transform'])