交叉验证模型的预测概率

Question

我想用交叉验证的Logistic回归模型来预测概率。我知道你可以得到交叉验证分数，但是否可以从predict_proba返回值而不是分数？

# imports
from sklearn.linear_model import LogisticRegression
from sklearn.cross_validation import (StratifiedKFold, cross_val_score,
                                      train_test_split)
from sklearn import datasets

# setup data
iris = datasets.load_iris()
X = iris.data
y = iris.target

# setup model
cv = StratifiedKFold(y, 10)
logreg = LogisticRegression()

# cross-validation scores
scores = cross_val_score(logreg, X, y, cv=cv)

# predict probabilities
Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
logreg.fit(Xtrain, ytrain)
proba = logreg.predict_proba(Xtest)

Answer 1

有一个函数cross_val_predict为您提供预测值，但是“predict_proba”还没有这样的函数。也许我们可以选择。