Dav*_*ene 7 python classification machine-learning decision-tree scikit-learn
我有一个带有 Scikit-Learn 的基本决策树分类器:
#Used to determine men from women based on height and shoe size
from sklearn import tree
#height and shoe size
X = [[65,9],[67,7],[70,11],[62,6],[60,7],[72,13],[66,10],[67,7.5]]
Y=["male","female","male","female","female","male","male","female"]
#creating a decision tree
clf = tree.DecisionTreeClassifier()
#fitting the data to the tree
clf.fit(X, Y)
#predicting the gender based on a prediction
prediction = clf.predict([68,9])
#print the predicted gender
print(prediction)
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当我运行程序时,它总是输出“男性”或“女性”,但是我如何才能看到预测是男性还是女性的概率?例如,上面的预测返回“男性”,但我如何让它打印预测为男性的概率?
谢谢!
您可以执行以下操作:
from sklearn import tree
#load data
X = [[65,9],[67,7],[70,11],[62,6],[60,7],[72,13],[66,10],[67,7.5]]
Y=["male","female","male","female","female","male","male","female"]
#build model
clf = tree.DecisionTreeClassifier()
#fit
clf.fit(X, Y)
#predict
prediction = clf.predict([[68,9],[66,9]])
#probabilities
probs = clf.predict_proba([[68,9],[66,9]])
#print the predicted gender
print(prediction)
print(probs)
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理论
结果clf.predict_proba(X)是: 预测的类概率,即叶子中同一类样本的比例。
结果解读:
第一个print返回,['male' 'male']因此数据[[68,9],[66,9]]预测为males。
第二个print返回:
[[ 0. 1.]
[ 0. 1.]]
这意味着数据被预测为男性,这是由第二列中的数据报告的。
要查看类的顺序,请使用:clf.classes_
这将返回:['female', 'male']
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