How To Calculate Prediction Probability In Python And Nltk?

I am trying to calculate each prediction probability in SVM model by using LinearSVC and OneVsRestClassifier but getting the error AttributeError: 'LinearSVC' object has no attribu

Solution 1:

With your Linear SVM:

from sklearn.calibrationimportCalibratedClassifierCV
from sklearn.feature_extraction.textimportTfidfVectorizerfrom sklearn.pipelineimportFeatureUnion, make_pipeline
from sklearn.svmimportLinearSVC

word_vectorizer = TfidfVectorizer(ngram_range=(1, 2))
features = FeatureUnion([('words', word_vectorizer), ])
calibrated_svc = CalibratedClassifierCV(LinearSVC(), method='sigmoid', cv=3)
pipeline = make_pipeline(features, calibrated_svc)
pipeline.fit(train_x, train_y)
predicted = pipeline.predict_proba(test_x)

or with Logistic Regression:

from sklearn.feature_extraction.textimportTfidfVectorizerfrom sklearn.pipelineimportFeatureUnion, make_pipeline
from sklearn.linear_modelimportLogisticRegression

word_vectorizer = TfidfVectorizer(ngram_range=(1, 2))
features = FeatureUnion([('words', word_vectorizer), ])
pipeline = make_pipeline(features, LogisticRegression())
pipeline.fit(train_x, train_y)
predicted = pipeline.predict_proba(test_x)

Solution 2:

Simply because 'SKlearnClassifier' object has no attribute 'predict_proba'

You can predict probability this way,

 classifier.classify_many(test)

 for pdist in classifier.prob_classify_many(test):
...     print('%.4f %.4f' % (pdist.prob('x'), pdist.prob('y')))

code from here