def TrainAndTestMultiDigitsPerceptron():
digits = [i for i in xrange(0,10)]
print "Running the Multi Digits Perceptron"
print "the digits it shall descriminate between: "+digits.__str__()
print "Extracting the Training Data"
img,lbl = rn.getData(digits, "training")
print "Training the Multi Digit Perceptron:"
MulitDigitPerc = pr.MultiDigitPerceptron(digits,img,lbl,int(alpha*len(lbl)))
print "Error on the Training data: "
print str(pr.TestClassifier(img,lbl,MulitDigitPerc)*100.0)+"%"
print "Extracting the Testing Data"
img,lbl = rn.getData(digits, "testing")
print "False Classification on the Testing data: "+str(pr.TestClassifier(img,lbl,MulitDigitPerc)*100.0)+"%"
def TrainAndTestWeakMultiDigitPerceptron():
digits = [i for i in xrange(0,10)]
print "Running the Weak Multi Digit Perceptron"
fullimg,lbl = rn.getData(digits, "training")
reducedList = rn.getReductionList(colnum, rownum)
img = rn.ReduceSetDimension(reducedList, fullimg)
perc = pr.MultiDigitPerceptron(digits,img,lbl,int(alpha*len(lbl)))
print "Error on the Training data: "+str(pr.TestClassifier(img,lbl,perc)*100.0)+"%"
print "(out of "+str(len(lbl))+" samples)"
print "Extracting the Testing Data"
fullimg,lbl = rn.getData(digits, "testing")
img = rn.ReduceSetDimension(reducedList, fullimg)
print "Error on the Testing data: "+str(pr.TestClassifier(img,lbl,perc)*100.0)+"%"
print "(out of "+str(len(lbl))+" samples)"
def TrainAndTestMultiDigitsPerceptron():
digits = [i for i in xrange(0, 10)]
print "Running the Multi Digits Perceptron"
print "the digits it shall descriminate between: " + digits.__str__()
print "Extracting the Training Data"
img, lbl = rn.getData(digits, "training")
print "Training the Multi Digit Perceptron:"
MulitDigitPerc = pr.MultiDigitPerceptron(digits, img, lbl,
int(alpha * len(lbl)))
print "Error on the Training data: "
print str(pr.TestClassifier(img, lbl, MulitDigitPerc) * 100.0) + "%"
print "Extracting the Testing Data"
img, lbl = rn.getData(digits, "testing")
print "False Classification on the Testing data: " + str(
pr.TestClassifier(img, lbl, MulitDigitPerc) * 100.0) + "%"
def TrainAndTestBinPerceptron():
if len(digits)>2:
print "digits should be 2 digits in the case of Binary Perceptron"
print "Running the Binary Perceptron"
print "the digits it shall descriminate between: "+str(digits[0])+","+str(digits[1])
print "the label 1 will be given to the digit "+str(digits[0])
img,lbl = rn.getData(digits, "training")
binlbl=rn.BinaryLabels(lbl,digit)
perc = pr.Perceptron(img,binlbl,int(alpha*len(binlbl)))
print "Error on the Training data: "+str(pr.TestClassifier(img, binlbl,perc)*100.0)+"%"
print "(out of "+str(len(binlbl))+" samples)"
print "Extracting the Testing Data"
img,lbl = rn.getData(digits, "testing")
binlbl=rn.BinaryLabels(lbl,digit)
print "Error on the Testing data: "+str(pr.TestClassifier(img,binlbl,perc)*100.0)+"%"
print "(out of "+str(len(binlbl))+" samples)"
def TrainAndTestWeakMultiDigitPerceptron():
digits = [i for i in xrange(0, 10)]
print "Running the Weak Multi Digit Perceptron"
fullimg, lbl = rn.getData(digits, "training")
reducedList = rn.getReductionList(colnum, rownum)
img = rn.ReduceSetDimension(reducedList, fullimg)
perc = pr.MultiDigitPerceptron(digits, img, lbl, int(alpha * len(lbl)))
print "Error on the Training data: " + str(
pr.TestClassifier(img, lbl, perc) * 100.0) + "%"
print "(out of " + str(len(lbl)) + " samples)"
print "Extracting the Testing Data"
fullimg, lbl = rn.getData(digits, "testing")
img = rn.ReduceSetDimension(reducedList, fullimg)
print "Error on the Testing data: " + str(
pr.TestClassifier(img, lbl, perc) * 100.0) + "%"
print "(out of " + str(len(lbl)) + " samples)"
def TrainAndTestWeakBinPerceptron():
if len(digits)>2:
print "digits should be 2 digits in the case of Binary Perceptron"
print "Running the Weak Binary Perceptron"
print "the digits it shall descriminate between: "+str(digits[0])+","+str(digits[1])
fullimg,lbl = rn.getData(digits, "training")
binlbl=rn.BinaryLabels(lbl,digit)
reducedList = rn.getReductionList(colnum, rownum)
img = rn.ReduceSetDimension(reducedList, fullimg)
perc = pr.Perceptron(img,binlbl,int(alpha*len(binlbl)))
print "Error on the Training data: "+str(pr.TestClassifier(img, binlbl,perc)*100.0)+"%"
print "(out of "+str(len(binlbl))+" samples)"
print "Extracting the Testing Data"
fullimg,lbl = rn.getData(digits, "testing")
img = rn.ReduceSetDimension(reducedList, fullimg)
binlbl=rn.BinaryLabels(lbl,digit)
print "Error on the Testing data: "+str(pr.TestClassifier(img,binlbl,perc)*100.0)+"%"
print "(out of "+str(len(binlbl))+" samples)"
def TrainAndTestBinPerceptron():
if len(digits) > 2:
print "digits should be 2 digits in the case of Binary Perceptron"
print "Running the Binary Perceptron"
print "the digits it shall descriminate between: " + str(
digits[0]) + "," + str(digits[1])
print "the label 1 will be given to the digit " + str(digits[0])
img, lbl = rn.getData(digits, "training")
binlbl = rn.BinaryLabels(lbl, digit)
perc = pr.Perceptron(img, binlbl, int(alpha * len(binlbl)))
print "Error on the Training data: " + str(
pr.TestClassifier(img, binlbl, perc) * 100.0) + "%"
print "(out of " + str(len(binlbl)) + " samples)"
print "Extracting the Testing Data"
img, lbl = rn.getData(digits, "testing")
binlbl = rn.BinaryLabels(lbl, digit)
print "Error on the Testing data: " + str(
pr.TestClassifier(img, binlbl, perc) * 100.0) + "%"
print "(out of " + str(len(binlbl)) + " samples)"
def TrainAndTestWeakBinPerceptron():
if len(digits) > 2:
print "digits should be 2 digits in the case of Binary Perceptron"
print "Running the Weak Binary Perceptron"
print "the digits it shall descriminate between: " + str(
digits[0]) + "," + str(digits[1])
fullimg, lbl = rn.getData(digits, "training")
binlbl = rn.BinaryLabels(lbl, digit)
reducedList = rn.getReductionList(colnum, rownum)
img = rn.ReduceSetDimension(reducedList, fullimg)
perc = pr.Perceptron(img, binlbl, int(alpha * len(binlbl)))
print "Error on the Training data: " + str(
pr.TestClassifier(img, binlbl, perc) * 100.0) + "%"
print "(out of " + str(len(binlbl)) + " samples)"
print "Extracting the Testing Data"
fullimg, lbl = rn.getData(digits, "testing")
img = rn.ReduceSetDimension(reducedList, fullimg)
binlbl = rn.BinaryLabels(lbl, digit)
print "Error on the Testing data: " + str(
pr.TestClassifier(img, binlbl, perc) * 100.0) + "%"
print "(out of " + str(len(binlbl)) + " samples)"