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
