''' 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 ''' modelfile = path + '/models/modelDict_%d.model'%numberFE trainAveragesFile = path+'/models/trainAverages_%d.model'%numberFE applyFE(path, modelfile, trainAveragesFile, 20000000000) ''' 8) run_applySentimentMF.py ''' applySMF(path, 50000) '''
import sys
sys.path.append('../')
import logging
import time
from sentimentAggregation.learnAggregationModel import learnAggreationModel
if __name__ == '__main__':
logger = logging.getLogger('signature')
logfile = '../../data/log/%d_learnAggreationModel.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/'
learnAggreationModel(path,20000)
