2) run_sampler.py ''' sampler(path+'/yelp_reviews_features.json', [0.4,0.8], 4) ''' 3) importantFeaturesIdentification.py ''' importantFeatureIdentification(path+'/yelp_reviews_features_stat.json', path+'/businessFeaturesAggregation_train.json', path+'/userFeaturesAggregation_train.json', True,True,1000000000) ''' 4) run_learnFeatureExistence.py ''' numberFE = learnFE(path, 10000000000) exit() ''' 5) run_learnSentimentMF.py ''' learnSentimentMF(path,2000000000) ''' 6) run_learnAggregationModel.py ''' numberAM = learnAggreationModel(path,2000000000) ''' 7) run_applyFeatureExistance.py '''
import sys sys.path.append('../') import logging import time from featureWorkers.learnFeaturesExistence import learnFE from params.params import path if __name__ == '__main__': logger = logging.getLogger('signature') logfile = '../../data/log/%d_learnFE.log'%int(time.time()) logging.basicConfig(filename = logfile, format='%(asctime)s : %(name)-12s: %(levelname)s : %(message)s') logging.root.setLevel(level=logging.DEBUG) logger.info("running %s" % ' '.join(sys.argv)) console = logging.StreamHandler() console.setLevel(logging.DEBUG) # set a format which is simpler for console use formatter = logging.Formatter('%(asctime)s : %(name)-12s: %(levelname)-8s %(message)s') # tell the handler to use this format console.setFormatter(formatter) logger.addHandler(console) #path = '../../data/restaurants' #path = '../../data/beautyspa' learnFE(path, 10000000000)