Example code snippet for Naive Bayes fundamentals article, part [4]

bayes_std.py

def std(x, mu):
    # calculate standard deviation (in reality np.std(x))
    return np.sqrt(sum(np.power(np.subtract(x, mu), 2)) / len(x))

std_less = np.std(less, mean_less)
std_more = np.std(more, mean_more)  # calculate standard deviation for both models