【已解决】TypeError: __init__() got an unexpected keyword argument ‘min_impurity_split‘

建立随机森林模型

随机森林是若干决策树组成的集成模型，训练速度较快，性能也较好。

在此不加调优的指定随机森林的相关超参数防止过拟合：

• 参数n_estimators：指定随机森林中决策树的数量为100；
• 参数max_depth：指定决策树的最大深度为5；
• 参数min_samples_leaf：指定决策树的叶子节点至少要包含100个样本。

clf = RandomForestClassifier(n_estimators = 100, max_depth = 5, min_samples_leaf = 100)
clf.fit(X_train, y_train)

RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
                       max_depth=5, max_features='auto', max_leaf_nodes=None,
                       min_impurity_decrease=0.0, min_impurity_split=None,
                       min_samples_leaf=100, min_samples_split=2,
                       min_weight_fraction_leaf=0.0, n_estimators=100,
                       n_jobs=None, oob_score=False, random_state=None,
                       verbose=0, warm_start=False)

报错：

Traceback (most recent call last):
  File "E:\python\hotal\2.py", line 194, in 
    RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
TypeError: __init__() got an unexpected keyword argument 'min_impurity_split'

类型错误：__init__（）获得了意外的关键字参数“min_impurity_split”

解决方法：

参考了：__init__() got an unexpected keyword argument 'min_impurity_split - CSDN文库

直接删除了 min_impurity_split

代码正常运行