def load_model(): corpus = pcc.PostagCorpus() corpus.load_corpus(MODEL_DIR) features = exfc.ExtendedFeatures(corpus) features.load_features(MODEL_DIR + "features.txt", corpus) model = spc.StructuredPercetron(corpus, features) model.load_model(MODEL_DIR) return corpus, features, model
def train_pos(corpus, features): model = spc.StructuredPercetron(corpus, features) model.nr_rounds = 10 model.train_supervised(corpus.sequence_list.seq_list) model.save_model(MODEL_DIR) return model