我在学习机器学习中的RandomizedSearchCV。

代码如下：

data = pd.read_csv("heart-disease.csv")data_shuffled = data.sample(frac = 1)X = data_shuffled.drop("target", axis = 1)y = data_shuffled["target"]X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2)grid = {"n_estimators": [10, 100, 200, 500, 1000, 1200],        "max_depth": [None, 5, 10, 15, 20, 30],        "max_featuers": ["auto", "sqrt"],        "min_samples_split": [2, 4, 6],        "min_samples_leaf": [1, 2, 4]}rfc = RandomForestClassifier(n_jobs = -1)rscv = RandomizedSearchCV(estimator = rfc,                          param_distributions=grid,                          n_iter = 100,                          cv = 5,                          verbose = 1)rscv.fit(X_train, y_train)

我遇到的错误是：

ValueError: Invalid parameter max_featuers for estimator RandomForestClassifier(min_samples_leaf=2, min_samples_split=6,                       n_estimators=1200, n_jobs=-1). Check the list of available parameters with `estimator.get_params().keys()`.

我检查了RandomForestClassifier库，想看看是否传递了错误的超参数名称，但没有发现任何问题。

回答：

你在参数网格的定义中有一个拼写错误：应该使用max_features而不是max_featuers。

grid = {    "n_estimators": [10, 100, 200, 500, 1000, 1200],    "max_depth": [None, 5, 10, 15, 20, 30],    "max_features": ["auto", "sqrt"],  # <-- 此处更改    "min_samples_split": [2, 4, 6],    "min_samples_leaf": [1, 2, 4]}