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])