compute confusion matrix using python

1import numpy as np
2
3currentDataClass = [1, 3, 3, 2, 5, 5, 3, 2, 1, 4, 3, 2, 1, 1, 2]
4predictedClass = [1, 2, 3, 4, 2, 3, 3, 2, 1, 2, 3, 1, 5, 1, 1]
5
6def comp_confmat(actual, predicted):
7
8    classes = np.unique(actual) # extract the different classes
9    matrix = np.zeros((len(classes), len(classes))) # initialize the confusion matrix with zeros
10
11    for i in range(len(classes)):
12        for j in range(len(classes)):
13
14            matrix[i, j] = np.sum((actual == classes[i]) & (predicted == classes[j]))
15
16    return matrix
17
18comp_confmat(currentDataClass, predictedClass)
19
20array([[3., 0., 0., 0., 1.],
21       [2., 1., 0., 1., 0.],
22       [0., 1., 3., 0., 0.],
23       [0., 1., 0., 0., 0.],
24       [0., 1., 1., 0., 0.]])
25
26