def classifier_test(classifier, feature_vector, mu_ft, std_ft):
    """
    Test the classifier on new data points.
    
    Arguments
    classifier: trained classifier (scikit object)
    feature_vector: np.array of shape [number of feature points; number of different features]
    mu_ft, std_ft: normalization parameters for the data
    
    Output
    y_hat: decision of the classifier on the data points
    """
    
    # Normalize feature_vector
    x = (feature_vector - mu_ft) / std_ft    
    y_hat = classifier.predict(x)
    #y_hat = None
    return y_hat