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