多标签二值化器-获得逆变换 [英] Multilabel binarizer - getting the inverse transform

问题描述

我坚持在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)

I am stuck on using the Multilabel binarizer and One-vs-all classifier in scikit-learn . My challenge is once I obtain the predictions, to obtain the original labels. (I trained and pickled the one-vs-rest classifier and vectorizer separately)

_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

谢谢您的帮助！

推荐答案

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

有关更多信息，请参见:多标签Binarizer

More on it is here: Multilabel Binarizer

这篇关于多标签二值化器-获得逆变换的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！