def Assignment2(): modelDic = {} confusionMatrix, trainMatrix = Mat.CreateConfusionMatrixs(10) # Fill dics for numbers 0..9 for i in range(0, 10): modelDic.update({i: {}}) numberVectorDic = VC.GetNumberVectors(testDataIn, testDataOut) VC.GetNumberAverageAndRadius(numberVectorDic, modelDic) print("Train set") TestModel(modelDic, trainDataIn, trainDataOut, confusionMatrix=trainMatrix) # PrintMatrix(trainMatrix,"train") print("Test set") TestModel(modelDic, testDataIn, testDataOut, confusionMatrix)
def Assignment3(n1, n2): trainMatrix, testMatrix = mat.CreateConfusionMatrixs(10) numberVectorDic = VC.GetNumberVectors(testDataIn, testDataOut) classChance = CalculateClassChance() histograms = ut.ExtractFeatures(numberVectorDic, binSize) #calculateAcurracy(histograms,classChance) for i in range(10): his1 = histograms[i][0] for j in range(i, 10): his2 = histograms[j][0] trainMatrix[j][i] = round( ut.histogram_intersection_chance(his1, his2, binSize), 1) trainMatrix[i][j] = round( ut.histogram_intersection_chance(his2, his1, binSize), 1) print("compare " + str(i) + " and " + str(j) + ": " + str(ut.histogram_intersection_chance(his1, his2, binSize))) mat.PrintMatrix(trainMatrix, "hisIntersection")