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")
