classify.py 文件源码

def eval_perf(classification):
    y_true = []
    y_pred = []

    for (key, value) in classification.iteritems():
        y_true.extend([parse_class(key)])
        y_pred.extend([value])

        print_verbose("Classification pair: %s" % str((key, value)), 4)
        print_verbose("True classes: %s" % str(y_true), 5)
        print_verbose("Predicted classes: %s" % str(y_pred), 5)

    # Print results
    print_verbose("True classes: %s" % str(y_true), 2)
    print_verbose("Predicted classes: %s" % str(y_pred), 2)

    # Print metrics
    print_verbose("Confusion Matrix:", 0)
    print_verbose(metrics.confusion_matrix(y_true, y_pred), 0)
    print_verbose("Classification Report:", 0)
    print_verbose(metrics.classification_report(y_true, y_pred), 0)