How can i know sample's probability that it belongs to a class predicted by predict() function of Scikit-Learn in Support Vector Machine?
>>>print clf.predict([fv])
[5]
There is any function?
Definitely read this section of the docs as there's some subtleties involved. See also Scikit-learn predict_proba gives wrong answers
Basically, if you have a multi-class problem with plenty of data predict_proba as suggested earlier works well. Otherwise, you may have to make do with an ordering that doesn't yield probability scores from decision_function.
Here's a nice motif for using predict_proba to get a dictionary or list of class vs probability:
model = svm.SVC(probability=True)
model.fit(X, Y)
results = model.predict_proba(test_data)[0]
# gets a dictionary of {'class_name': probability}
prob_per_class_dictionary = dict(zip(model.classes_, results))
# gets a list of ['most_probable_class', 'second_most_probable_class', ..., 'least_class']
results_ordered_by_probability = map(lambda x: x[0], sorted(zip(model.classes_, results), key=lambda x: x[1], reverse=True))