def bayes_test(args): ''' Function starts test of bayesian classifier with given dataset and classifier parameters. ''' bt = BayesianTest(dbfile=args.db_file, max_token_size=args.max_token_size) if args.feats is not None: features = eval(args.feats) if isinstance(features,dict): e = Entry(id=None, guid=None, entry=None, language=None) if not e.check_feats(features): print 'Incorrect format of feature dictionary' return else: features = bt.get_best_features(count=args.count, n_fold_cv=args.n_fold_cv) bt.run(features=features, count=args.count, n_fold_cv=args.n_fold_cv)
def _thread_bayes(db_file, count, n_fold_cv, max_token_size): from src.bayes.bayesian_test import BayesianTest bt = BayesianTest(dbfile=db_file, max_token_size=max_token_size) # run feature selection features = bt.get_best_features(count=count, n_fold_cv=n_fold_cv) # run test with best features result = bt.run(features=features, count=count, n_fold_cv=n_fold_cv) # return results return {'type':'bayes', 'result': result, 'features':features}