Multiclass Confusion Matrix

Problem

Build a multiclass confusion matrix: counts[i][j] is the number of samples with true label i and predicted label j.

Pairs outside [0, num_classes) are ignored. Empty input returns a num_classes x num_classes matrix of zeros.

Hint

Row index is the true class and column index is the predicted class.

case 1

in: [[0,1,2,1,0],[0,2,2,1,1],3]

expected: [[1,1,0],[0,1,1],[0,0,1]]

case 2

in: [[0,1,2],[0,1,2],3]

expected: [[1,0,0],[0,1,0],[0,0,1]]

case 3

in: [[0,3],[0,0],2]

expected: [[1,0],[0,0]]

case 4

in: [[],[],2]

expected: [[0,0],[0,0]]

Starter codePython

def multiclass_confusion_matrix(y_true, y_pred, num_classes):
    # Your code here
    pass

4 test cases · run your code against them in the editor