def parse(self):
# Data Processing
for row in self.spamreader:
temp=[]
for i in range(0,len(row)):
if(self.pFeatures[i]==1):
temp+=[int(float(self.mapDefine((self.pHeader[i]),row[i])))]
self.pData+=[temp]
HF=dataRecovery.holesFiller('LinearRegression');
HF.feedData(self.featureFilter(self.pFeatures,self.pHeader),self.pData,'age');
Y=HF.fillData();
return Y;
def dump(self):
HF = dataRecovery.holesFiller("LinearRegression")
HF.feedData(self.featureFilter(self.fMapTrain, self.TrainHeader), self.data, "age")
Y = HF.fillData()
with open("DATA/pnewtrain_v2.csv", "wb") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=",", quotechar='"')
self.fMapTrain[self.mainF] = 1
pHeader = self.featureFilter(self.fMapTrain, self.TrainHeader)
print(pHeader)
csvwriter.writerow(pHeader)
for i in range(0, self.TrainCount):
csvwriter.writerow([self.TrainXtra[i]] + Y[i])
with open("DATA/pnewtest_v2.csv", "wb") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=",", quotechar='"')
pHeader = self.featureFilter(self.fMapTest, self.TestHeader)
print(pHeader)
csvwriter.writerows([pHeader] + Y[self.TrainCount : self.TestCount + self.TrainCount])