def integrator():
K=5
Preprocessing.main()
Boostrap.main(Preprocessing.inputSet)
#print(Boostrap.testSet)
global prediction
prediction={}
#bootstrapVoting
for i in range(Boostrap.NO_OF_BOOTSTRAPS):
print("*** %d BootStrap ****" %(i))
#prediction[i]=KNN.main(Boostrap.bootstrap[i],Boostrap.testSet,K)
(inputToRectifier,probabilityChart, priors, featureAndValues, trainSetLength)=NaiveBayes.NaiveBayes(Boostrap.bootstrap[i])
print("********DECIION TREE************")
tree=DecisionTree.GenerateTreeFromDatasetGivenByAssorter(inputToRectifier)
print("********DECIION TREE ENDS************")
print("********TEST NAIVE START************")
probabilityDistributionChart=NaiveBayes.GetProbabilityDistributionTable(probabilityChart, priors, featureAndValues, Boostrap.testSet,trainSetLength)
print("********TEST NAIVE ENDS************")
print("********PREDICTION START************")
prediction[i]=DecisionTree.PredictedList(probabilityDistributionChart,tree,Boostrap.testSet)
#print("***prediction***",prediction)
print("*********** BootStrapVoting *************")
boostrapVoting()
calculateTestError()
