def preprocessing(StemmedDict,fileName):
v = set()
f = open(fileName,'r')
for line in f:
line = line.strip()
#print line
lineCleaned = Cleaner.getProcessedData(line,1)
#print lineCleaned
Id = lineCleaned.split('\x01')[0]
lineStem = StemmerClass.Stemmer()
if not Id in v:
v.add(Id)
StemmedDict[Id] = lineStem.getStemmedCorpus(lineCleaned)
def createFeature(fileName, docRumourScore,docFactScore,classLabel):
f = open(fileName,'r')
rmax = max(docRumourScore.itervalues())
rmin = min(docRumourScore.itervalues())
lmax = max(docFactScore.itervalues())
lmin = min(docFactScore.itervalues())
for line in f:
line = line.strip()
#print line
lineCleaned = Cleaner.getProcessedData(line,1)
data = lineCleaned.split('\x01')
id = data[0]
rumorScore = docRumourScore[id]
factScore = docFactScore[id]
liscence = 0 if data[3] == 'false' else 1
defination = 0 if data[4] == 'sd' else 1
views = float(data[5])
print id+','+str((rumorScore-rmin)/rmax)+','+str((factScore-lmin)/lmax)+','+str(liscence)+','+str(defination)+','+str(float(data[6])/views)+','+str(float(data[7])/views)+','+str(float(data[8])/views)+','+str(float(data[9])/views)+","+str(classLabel)
