def train(X_train, y_train, **kwargs):
    '''
    >>> corpus = CorpusReader('annot.opcorpora.xml')
    >>> X_train, x_test, y_train, y_test = get_train_data(corpus, test_size=0.33, random_state=42)
    >>> crf = train(X_train, y_train)
    '''
    crf = Trainer()
    crf.set_params({
        'c1': 1.0,
        'c2': 0.001,
        'max_iterations': 200,
        'feature.possible_transitions': True,
    })

    for xseq, yseq in zip(X_train, y_train):
        crf.append(xseq, yseq)
    crf.train(TOKENIZATION_MODEL_PATH)
    return crf
def train ( X_train , y_train , ** kwargs ) : crf = Trainer ( ) crf . set_params ( { 'c1' : 1.0 , 'c2' : 0.001 , 'max_iterations' : 200 , 'feature.possible_transitions' : True , } ) for xseq , yseq in zip ( X_train , y_train ) : crf . append ( xseq , yseq ) crf . train ( TOKENIZATION_MODEL_PATH ) return crf
>>> corpus = CorpusReader('annot.opcorpora.xml')
    >>> X_train, x_test, y_train, y_test = get_train_data(corpus, test_size=0.33, random_state=42)
    >>> crf = train(X_train, y_train)