y_train = [[0], [0], [0], [0], [0], [0], [1], [1], [1], [1], [1], [1], [0, 
    1], [0, 1]]
X_test = np.array(['nice day in nyc', 'welcome to london',
    'hello welcome to new york. enjoy it here and london too'])
target_names = ['New York', 'London']
classifier = Pipeline([('vectorizer', CountVectorizer(min_n=1, max_n=2)), (
    'tfidf', TfidfTransformer()), ('clf', OneVsRestClassifier(LinearSVC()))])
classifier.fit(X_train, y_train)
predicted = classifier.predict(X_test)
for item, labels in zip(X_test, predicted):
    pass
use scikit-learn to classify into multiple categories