acc = TestAccuracy(semisup_classifier, classA_test, classB_test, thresh) print 'accuracy {0}'.format(acc) segfun = semisup_classifier.segfun with open("../models/init_nonum_semi%i.pkl" % (iter_num + 1), 'w') as f: semisup_classifier.segfun = None cPickle.dump(semisup_classifier, f) semisup_classifier.segfun = segfun return semisup_classifier if __name__ == '__main__': target = 'gender' whereclause = "where gender is not ''" if target == 'gender' else '' model = segmenter.load_model('../models/idmorphs_naworl.model') segfun = segmenter.morph_segmenter(model, match='[a-z]+') # model_semi = segmenter.load_model('../models/idmorphs.model') # segfun_semi = segmenter.morph_segmenter(model_semi, match='[a-z]+') users = segmenter.get_users_from_db(whereclause=whereclause) male_ids = [user.id for user in users if user.gender == 'M'] female_ids = [user.id for user in users if user.gender == 'F'] # unlabeled_users = segmenter.get_users_from_db(tablename='naver') # unknown_ids = [user.id for user in unlabeled_users] unknown_ids = None cls = DoTest(male_ids, female_ids, segfun, unknown_ids, balance=False) # cls = cPickle.load(open("../models/init_nonum_semi3.pkl"))
__author__ = 'hee' import pytagcloud import segmenter if __name__ == '__main__': # model_path = "../models/idmorphs_naworl.model" model_path = "../models/okcupid.model" model = segmenter.load_model(model_path) top_morphs = segmenter.top_morphs(model, 100, exclude_number=True, min_length=2) tags = pytagcloud.make_tags(top_morphs, maxsize=130) print "here" pytagcloud.create_tag_image(tags, "../results/okcupid.bmp", size=(900, 600), rectangular=False)