Scikit learn SVC predict probability doesn't work as expected

Question

I built sentiment analyzer using SVM classifier. I trained model with probability=True and it can give me probability. But when I pickled my model and load it again later, the probability doesn't work anymore.

The model:

from sklearn.svm import SVC, LinearSVC
pipeline_svm = Pipeline([
    ('bow', CountVectorizer()),
    ('tfidf', TfidfTransformer()),
    ('classifier', SVC(probability=True)),])

# pipeline parameters to automatically explore and tune
param_svm = [
  {'classifier__C': [1, 10, 100, 1000], 'classifier__kernel': ['linear']},
  {'classifier__C': [1, 10, 100, 1000], 'classifier__gamma': [0.001, 0.0001], 'classifier__kernel': ['rbf']},
]

grid_svm = GridSearchCV(
    pipeline_svm,
    param_grid=param_svm,
    refit=True,
    n_jobs=-1, 
    scoring='accuracy',
    cv=StratifiedKFold(label_train, n_folds=5),)

svm_detector_reloaded = cPickle.load(open('svm_sentiment_analyzer.pkl', 'rb'))
print(svm_detector_reloaded.predict([""""Today is awesome day"""])[0])

Gives me:

AttributeError: predict_proba is not available when probability=False

Answer 1

Use: SVM(probability=True)

or

grid_svm = GridSearchCV(
    probability=True
    pipeline_svm,
    param_grid=param_svm,
    refit=True,
    n_jobs=-1, 
    scoring='accuracy',
    cv=StratifiedKFold(label_train, n_folds=5),)

Answer 2

Adding (probability=True) while initializing the classifier as someone above suggested, resolved my error:

clf = SVC(kernel='rbf', C=1e9, gamma=1e-07, probability=True).fit(xtrain,ytrain)