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)
