Exemple #1
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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) + "%"
Exemple #2
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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)"
Exemple #3
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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)"
Exemple #4
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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)"