def accuracy_score(y_true, y_pred):
    """
    Classification performance metric that computes the accuracy of y_true
    and y_pred.

    :param numpy.array y_true: array-like of shape (n_samples,) Ground truth correct labels.
    :param numpy.array y_pred: array-like of shape (n_samples,) Estimated target values.
    :returns: C (float) Accuracy score.
    """
    correct = 0
    for true, pred in zip(y_true, y_pred):
        if true == pred:
            correct += 1
    accuracy = correct / len(y_true)
    return accuracy