用KNN算法对鸢尾花进行分类,添加网格搜索和交叉验证
def knn_iris_gscv(): """ 用KNN算法对鸢尾花进行分类,添加网格搜索和交叉验证 :return: """ # 1)获取数据 iris = load_iris() # 2)划分数据集 x_train, x_test, y_train, y_test = train_test_split(iris.data, iris.target, random_state=22) # 3)特征工程:标准化 transfer = StandardScaler() x_train = transfer.fit_transform(x_train) x_test = transfer.transform(x_test) # 4)KNN算法预估器 estimator = KNeighborsClassifier() # 加入网格搜索与交叉验证 # 参数准备 param_dict = {"n_neighbors": [1, 3, 5, 7, 9, 11]} estimator = GridSearchCV(estimator, param_grid=param_dict, cv=10) estimator.fit(x_train, y_train) # 5)模型评估 # 方法1:直接比对真实值和预测值 y_predict = estimator.predict(x_test) print("y_predict:\n", y_predict) print("直接比对真实值和预测值:\n", y_test == y_predict) # 方法2:计算准确率 score = estimator.score(x_test, y_test) print("准确率为:\n", score) # 最佳参数:best_params_ print("最佳参数:\n", estimator.best_params_) # 最佳结果:best_score_ print("最佳结果:\n", estimator.best_score_) # 最佳估计器:best_estimator_ print("最佳估计器:\n", estimator.best_estimator_) # 交叉验证结果:cv_results_ print("交叉验证结果:\n", estimator.cv_results_) return None