与sklearn

Question

预测多标记数据。根据文档时，OneVsRest分类支持多标签分类：http://scikit-learn.org/stable/modules/multiclass.html#multilabel-learning

这里是我试图运行代码：

from sklearn import metrics 
from sklearn.preprocessing import MultiLabelBinarizer 
from sklearn.multiclass import OneVsRestClassifier 
from sklearn.cross_validation import train_test_split 
from sklearn.svm import SVC 

x = [[1,2,3],[3,3,2],[8,8,7],[3,7,1],[4,5,6]] 
y = [['bar','foo'],['bar'],['foo'],['foo','jump'],['bar','fox','jump']] 

y_enc = MultiLabelBinarizer().fit_transform(y) 

train_x, train_y, test_x, test_y = train_test_split(x, y_enc, test_size=0.33) 

clf = OneVsRestClassifier(SVC()) 
clf.fit(train_x, train_y) 
predictions = clf.predict_proba(test_x) 

my_metrics = metrics.classification_report(test_y, predictions) 
print my_metrics 

我收到以下错误：

Traceback (most recent call last): 
    File "multilabel.py", line 178, in <module> 
    clf.fit(train_x, train_y) 
    File "/sklearn/lib/python2.6/site-packages/sklearn/multiclass.py", line 277, in fit 
    Y = self.label_binarizer_.fit_transform(y) 
    File "/sklearn/lib/python2.6/site-packages/sklearn/base.py", line 455, in fit_transform 
    return self.fit(X, **fit_params).transform(X) 
    File "/sklearn/lib/python2.6/site-packages/sklearn/preprocessing/label.py", line 302, in fit 
    raise ValueError("Multioutput target data is not supported with " 
ValueError: Multioutput target data is not supported with label binarization 

不使用MultiLabelBinarizer给出了相同的错误，所以我假设这不是问题。有谁知道如何将这个分类器用于多标签数据？

Answer 1

您的train_test_split()输出不正确。改变这一行：

train_x, train_y, test_x, test_y = train_test_split(x, y_enc, test_size=0.33)

要这样：

train_x, test_x, train_y, test_y = train_test_split(x, y_enc, test_size=0.33)

此外，使用概率，而不是类的预测，您需要更改SVC()到SVC(probability = True)和更改clf.predict_proba到clf.predict。

全部放在一起：

from sklearn import metrics 
from sklearn.preprocessing import MultiLabelBinarizer 
from sklearn.multiclass import OneVsRestClassifier 
from sklearn.cross_validation import train_test_split 
from sklearn.svm import SVC 


x = [[1,2,3],[3,3,2],[8,8,7],[3,7,1],[4,5,6]] 
y = [['bar','foo'],['bar'],['foo'],['foo','jump'],['bar','fox','jump']] 

mlb = MultiLabelBinarizer() 
y_enc = mlb.fit_transform(y) 

train_x, test_x, train_y, test_y = train_test_split(x, y_enc, test_size=0.33) 

clf = OneVsRestClassifier(SVC(probability=True)) 
clf.fit(train_x, train_y) 
predictions = clf.predict(test_x) 

my_metrics = metrics.classification_report(test_y, predictions) 
print my_metrics 

这让我没有错误，当我运行它。

Answer 2

我还在OneVsRestClassifier中遇到过“ValueError：Multioutput目标数据不支持标签二进制化”。我的问题是由np.array（）投射后，训练数据的类型为“list”造成的。