python - 决策树——Python最有影响力的参数

Question

我有一个简单的 Python 决策树程序。有没有办法从 X 中找出(打印)导致结果的最有影响力的参数(或多个参数)？例如:“预测结果为"is"。最有影响的参数是X项中的[0]个值”

from sklearn import tree


X=[[100,3],[130,3],[80,2],[90,2],[140,3]]
Y=["yes","no","yes","yes","no"]

clf = tree.DecisionTreeClassifier()

clf = clf.fit(X,Y)

List1=[124,3]

prediction = clf.predict([List1])

print(prediction)

Answer 1

可以使用

feature_importances_属性。

The feature importances. The higher, the more important the feature. The importance of a feature is computed as the (normalized) total reduction of the criterion brought by that feature.

http://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html

print(clf.feature_importances_)
> [1. 0.]

这里第二个特征重要性为零，这意味着该特征不包含在规则树中。