我一直在scikit-learn中使用Multilabel binarizer和One-vs-all分类器。我的挑战是一旦获得预测,
获取原始标签。 (我分别训练和腌制了一对多休息分类器和矢量化器)

_labels = load_labels()
mlb = MultiLabelBinarizer()
mlb.fit_transform(_labels)
print mlb.classes_ # this prints the binarized labels

_clf,_vect = load_pickle('./pickles')

for q in queries:
    #query vector q
    X = vect.transform([q])
    res = clf.predict_proba(X)
    print res #[[ 0.00164113  0.00706595  0.00683465 .... 0.00837984]]

    #this is where I am stuck on what to pass into the inverse_transform to obtain
    preds = mlb.inverse_transform(??)
    print preds


感谢您的帮助!

最佳答案

mlb.fit_transform(_labels)的输出将是inverse_transform的输入。

有关更多信息,请参见:Multilabel Binarizer

关于python - Multilabel Binarizer-获得逆变换,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/47356433/

10-12 19:29