compute confusion matrix using python
import numpy as np currentDataClass = [1, 3, 3, 2, 5, 5, 3, 2, 1, 4, 3, 2, 1, 1, 2] predictedClass = [1, 2, 3, 4, 2, 3, 3, 2, 1, 2, 3, 1, 5, 1, 1] def comp_confmat(actual, predicted): classes = np.unique(actual) # extract the different classes matrix = np.zeros((len(classes), len(classes))) # initialize the confusion matrix with zeros for i in range(len(classes)): for j in range(len(classes)): matrix[i, j] = np.sum((actual == classes[i]) & (predicted == classes[j])) return matrix comp_confmat(currentDataClass, predictedClass) array([[3., 0., 0., 0., 1.], [2., 1., 0., 1., 0.], [0., 1., 3., 0., 0.], [0., 1., 0., 0., 0.], [0., 1., 1., 0., 0.]])