用随机森林做多分类 为啥得到的AUC总是1

Question

x_train,x_validation,y_train,y_validation = train_test_split(df.iloc[:,:-1],
                                                             df.iloc[:,-1],test_size=0.2)

rf = RandomForestClassifier(n_estimators=n_estimators_value,
                            max_depth=max_depth_value,
                            min_samples_leaf=min_samples_leaf_value,
                            min_samples_split=min_samples_split_value,
                            n_jobs=-1)
rf.fit(x_train,y_train)  # 训练分类器
result_y = rf.predict(x_validation)
#y_pred = np.rint(result_y)
auc = accuracy_score(result_y,y_validation)
return auc

Answer 1

是不是因为你的数据集比较简单，使用模型预测的准确率达到了100%