def excute(self): FinalList = [] Instance = Methods.MethodRepository() File = FileReader.File() lisst = File.FileRead() TraininD = lisst[0] TestD = lisst[1] TestSet = TestD TrainSet = TraininD self.Tset = TrainSet x = len(TraininD[0]) Test = Decimal(1) Data = [] Class = Instance.UniqueList(TraininD) for increment in range(x - 1): #Spilting Data i.e in training and testing #Count repetition of attribute per class Data = Instance.CountRepInClass(TraininD) self.D = Data AttributeList = Instance.Findings(TraininD, increment, Class) AttributeList = Instance.Filter(AttributeList, Class) Difference = Instance.CountDifferent(TraininD, increment) AttributeList = Instance.ZeroFreProblem(AttributeList, Difference) Total = Instance.Total(TraininD) self.T = Total Structure = Instance.MakeStruc(AttributeList, TraininD, increment) Difference = Instance.CountDifferent(TraininD, increment) Attributes = Difference Difference = len(Difference) C = Instance.PredictC(Structure, Total, Difference) X = Instance.PredictX(Structure, TraininD, Difference) XC = Instance.PredictXC(Structure, Data, Difference) PosterierP = Instance.PosterierP(C, XC, X, Attributes) FinalStruc = Instance.FinalStructure(PosterierP, Attributes) FinalList.append(FinalStruc) # print(AttributeList) #have to look here EvolveRes = Instance.EvolveAttP(FinalList, TestSet, Total) Total = len(TrainSet) - 1 POfClasses = Instance.findClassP(Total, Data) #ZeroFrequency =Instance.ZeroFreProblem(EvolveRes) Prediction = Instance.Predict(EvolveRes, POfClasses) Result = Instance.GivePrediction(Prediction) Accuracy = Instance.Accuracy(TestD, Result) #print ("Accuray:%s " %Accuracy) return Accuracy, FinalList