# run the trials
def run_trials(params, repeats=5):
    # test each parameter
    all_scores = list()
    for param in params:
        scores = list()
        for repeat in range(repeats):
            score = fit_evaluate_model(X_train, y_train, X_test, y_test, param)
            score = score * 100.0
            print('>Filter=%d #%d: %.3f' % (param, repeat+1, score))
            scores.append(score)
        all_scores.append(scores)
    performance_summary(all_scores, params)
 
# run 
n_filters = [8, 16, 32, 64, 128, 256]
run_trials(n_filters)