def __init__(self,
traing_data_fileP1='mood_traing_p1.dat',
traing_data_fileP2='mood_traing.dat',
data_file='tweets_raw.dat'):
if self.sentiwordnet:
print "using sentiwordnet dictionary"
else:
print "not using sentiwordnet dictionary"
self.clsP1 = MoodDetectTrainer(data_file=traing_data_fileP1)
self.clsP2 = MoodDetectTrainer(data_file=traing_data_fileP2)
self.langClassifier = LangDetect(supportedLangs)
self.training_data_p1 = MoodDetectTrainData()
self.training_data_p2 = MoodDetectTrainData()
self.tweetsFile = open(
os.path.join(os.curdir, os.path.normpath('../data/' + data_file)),
'rb')
self.countRows(self.tweetsFile)
self.tweetsFile = open(
os.path.join(os.curdir, os.path.normpath('../data/' + data_file)),
'rb')
self.limit['en'] = 300000
self.limit['default'] = 10000
self.count = 0
swn_filename = '../dict/sentiwordnet/' + conf.SENTIWORDNET_DICT_FILENAME
self.swn = SentiWordNetCorpusReader(swn_filename)
def __init__(self,
traing_data_fileP1='mood_traing_p1.dat',
traing_data_fileP2='mood_traing.dat',
data_file='tweets_raw.dat'):
self.clsP1 = MoodDetectTrainer(data_file=traing_data_fileP1)
self.clsP2 = MoodDetectTrainer(data_file=traing_data_fileP2)
self.langClassifier = LangDetect(supportedLangs)
self.training_data_p1 = MoodDetectTrainData()
self.training_data_p2 = MoodDetectTrainData()
self.tweetsFile = open(os.path.join(self.dataDir, data_file), 'rb')
self.countRows(self.tweetsFile)
self.tweetsFile = open(os.path.join(self.dataDir, data_file), 'rb')
self.limit['en'] = 150000
self.limit['default'] = 10000
self.count = 0
swn_filename = '../dict/sentiwordnet/SentiWordNet_3.0.0_20100705.txt'
self.swn = SentiWordNetCorpusReader(swn_filename)
def loadCls():
ThreadedTCPServer.langCls = LangDetect(supportedLangs)
ThreadedTCPServer.moodCls = MoodDetect(MoodDetectTrainer())
