tc_confusion_matrix.py

import turicreate as tc
import pandas as pd


def print_human_confusion_matrix(actual, predicted):
    cf_matrix = tc.evaluation.confusion_matrix(actual, predicted)

    labels = list(set(cf_matrix['predicted_label'].append(cf_matrix['target_label'])))

    matrix = []
    for predicted_label in labels:
        out_row = []
        for target_label in labels:
            row = cf_matrix[(cf_matrix['predicted_label']==predicted_label) & (cf_matrix['target_label']==target_label)]
            out_row.append(row['count'])

        matrix.append(out_row)

    print(pd.DataFrame(matrix, index=labels, columns=labels))

actual    = tc.SArray(["blue", "red", "silver", "silver", "red", "silver", "blue", "red"])
predicted = tc.SArray(["blue", "red", "blue", "silver", "red", "blue", "silver", "silver"])

print_human_confusion_matrix(actual, predicted)