How to write a confusion matrix in Python?

Question

I wrote a confusion matrix calculation code in Python:

def conf_mat(prob_arr, input_arr):
        # confusion matrix
        conf_arr = [[0, 0], [0, 0]]

            


        

Answer 1

This function creates confusion matrices for any number of classes.

def create_conf_matrix(expected, predicted, n_classes):
    m = [[0] * n_classes for i in range(n_classes)]
    for pred, exp in zip(predicted, expected):
        m[pred][exp] += 1
    return m

def calc_accuracy(conf_matrix):
    t = sum(sum(l) for l in conf_matrix)
    return sum(conf_matrix[i][i] for i in range(len(conf_matrix))) / t

In contrast to your function above, you have to extract the predicted classes before calling the function, based on your classification results, i.e. sth. like

[1 if p < .5 else 2 for p in classifications]