def Run_Q3_3_2_sp():
print '*********************************************************************************'
print "//Question-3.3.2 (Simple Perceptron-single pass) Report on Adult Data -----------------------------"
print '*********************************************************************************'
[XData, YData, FSize, SeenWt] = func.parseInfo(trainFileHandle)
maxVecLen = max(FSize)
margin = 0
for i in range(1, 2):
for j in LRateList:
[Bias, Wvec,
LearningMistake] = func.Perceptron(j, 1, XData, YData, maxVecLen,
i, margin, 0, SeenWt)
mistakeCount = func.TestPerceptron(XData, YData, Wvec, Bias,
maxVecLen, margin)
TrainAccuracy = (
(float(len(XData) - mistakeCount)) / len(XData)) * 100
print 'Using Learning Rate = ', j, ' number of epochs = Sinlge Pass, Initialization = random with mean 0 and sd 0.01'
# print '\t Learned Weight Vector = ', Wvec
print '\t Learned Bias = ', Bias
print '\t Mistakes during Learning = ', LearningMistake
print '\t Learning Accuracy = ', TrainAccuracy, '%\n'
if (test_index != -1):
[testXData,
testYData] = func.parseInfoTest(testFilehandle, maxVecLen)
testMistake = func.TestPerceptron(testXData, testYData, Wvec,
Bias, maxVecLen, margin)
TestAccuracy = ((float(len(testXData) - testMistake)) /
len(testXData)) * 100
print '\t Test Accuracy = ', TestAccuracy, '%\n'
print "//End of Question-3.3.2(simple Perceptron-single pass) Report ------------------------------------\n\n\n"
def Run_Q3_3_3_mp_batch_Shuffle():
print '***************************************************************************************************'
print "//Question-3.3.2 (Margin Perceptron-batch 3,4,5) With Shuffle Report on Adult Data -----------------------------"
print '***************************************************************************************************'
[XData, YData, FSize, SeenWt] = func.parseInfo(trainFileHandle)
maxVecLen = max(FSize)
for i in range(3, 6):
for j in LRateList:
for k in MarginList:
[Bias, Wvec,
LearningMistake] = func.Perceptron(j, 1, XData, YData,
maxVecLen, i, k, 0, SeenWt)
mistakeCount = func.TestPerceptron(XData, YData, Wvec, Bias,
maxVecLen, k)
TrainAccuracy = (
(float(len(XData) - mistakeCount)) / len(XData)) * 100
print 'Using Learning Rate = ', j, ', number of epochs = ', i, ' Margin = ', k, ', Initialization = random with mean 0 and sd 0.01, with shuffle'
# print '\t Learned Weight Vector = ', Wvec
print '\t Learned Bias = ', Bias
print '\t Mistakes during Learning = ', LearningMistake
print '\t Learning Accuracy = ', TrainAccuracy, '%\n'
if (test_index != -1):
[testXData,
testYData] = func.parseInfoTest(testFilehandle, maxVecLen)
testMistake = func.TestPerceptron(testXData, testYData,
Wvec, Bias, maxVecLen, k)
TestAccuracy = ((float(len(testXData) - testMistake)) /
len(testXData)) * 100
print '\t Test Accuracy = ', TestAccuracy, '%\n'
print "//End of Question-3.3.2(Margin Perceptron-Batch Mode-Shuffle) Report ------------------------------------\n\n\n"
def Run_Q3_3_1():
print '*********************************************************************************'
print "//Question-3.3.1 Report (Sanity check using Table2 -----------------------------"
print '*********************************************************************************'
[XData, YData, FSize, SeenWt] = func.parseInfo(sanityTable)
maxVecLen = max(FSize)
for i in range(1, 2):
for j in LRateList:
[Bias, Wvec,
LearningMistake] = func.Perceptron(j, 0, XData, YData, maxVecLen,
i, 0, 0, SeenWt)
mistakeCount = func.TestPerceptron(XData, YData, Wvec, Bias,
maxVecLen, 0)
TrainAccuracy = (float(len(XData) - mistakeCount) /
len(XData)) * 100
print 'Using Learning Rate = ', j, ' number of epochs = ', i, 'Initialization = @ default 0 , No-Shuffle'
print '\t Learned Weight Vector = ', Wvec
print '\t Learned Bias = ', Bias
print '\t Mistakes during Learning = ', LearningMistake
print '\t Learning Accuracy = ', TrainAccuracy, '%\n'
print "//End of Question-3.3.1 Report -------------------------------------------------\n\n"