xgb_classification.py 文件源码

def save_results(y_test, y_pred, labels, fold_number=0):
    pickle.dump(y_test, open("y_test_fold{number}.plk".format(number=fold_number), "w"))
    pickle.dump(y_pred, open("y_pred_fold{number}.plk".format(number=fold_number), "w"))
    print classification_report(y_test, y_pred)
    print confusion_matrix(y_test, y_pred)
    print "Micro stats:"
    print precision_recall_fscore_support(y_test, y_pred, average='micro')
    print "Macro stats:"
    print precision_recall_fscore_support(y_test, y_pred, average='macro')
    try:
        visualization.plot_confusion_matrix(confusion_matrix(y_test, y_pred),
                                            title="Test CM fold{number}".format(number=fold_number),
                                            labels=labels)
    except:
        pass