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1 from numpy import * 2 import random 3 import time 4 st = time.time() 5 6 def loaddata(filename): 7 fr = open(‘‘.join([filename, ‘.txt‘])).readlines() 8 trainx = [[1] + map(float, line.split()[:-1]) for line in fr] # trainx = [[1,12.2,22.4],[1,22.3,31.2],...] 9 trainy = [[float(line.split()[-1])] for line in fr] # trainy = [0,1,1,0,...] 10 return trainx, trainy 11 12 def sigmod(z): 13 return 1.0 / (1 + exp(-z)) 14 15 def optimizaion(trainx, trainy): 16 trainxmat = mat(trainx) 17 m = len(trainx) 18 # beta = [0,0,0] 19 beta = ones((len(trainx[0]),1)) # array 20 # maxiter 21 M = 500 22 """ 23 # error permid 24 e = 25 """ 26 """ 27 for i in xrange(M): 28 #if error2sum > e: 29 # z = betat.T * x = trainx (matricdoc)* beta = [beta.Tx1,beta.Tx2,...,beta.Txn] 30 sigmodz = sigmod(trainxmat * beta) 31 # [error_i = yi - sigmod(zi)] 32 error = trainy - sigmodz 33 # update beta 34 beta += alpha * trainxmat.T * error 35 print beta 36 """ 37 # random gradascent 38 for j in xrange(M): 39 for i in xrange(m): 40 # per span 41 alpha = 0.01 + 4 / (1.0 + i +j) 42 randid = random.randint(0, m - 1) 43 sigmodz = sigmod(trainxmat[randid] * beta) 44 error = trainy[randid] - sigmodz 45 beta += alpha * trainxmat[randid].T * error 46 #print beta 47 48 return beta 49 50 51 def logregress(testx, beta): 52 if mat(testx) * beta > 0: return [1.0] 53 else: return [0.0] 54 55 def main(): 56 # step 1: loading data... 57 print "step 1: loading data..." 58 trainx, trainy = loaddata(‘horseColicTraining‘) 59 testx, testy = loaddata(‘horseColicTest‘) 60 """ 61 print ‘trainx‘, trainx 62 print ‘trainy‘, trainy 63 print ‘testx‘, testx 64 print ‘testy‘, testy 65 print ‘testy[2]‘,testy[2] 66 """ 67 68 # step 2: training... 69 print "step 2: training..." 70 beta = optimizaion(trainx, trainy) 71 #print "beta = ",beta 72 73 # step 3: testing... 74 print "step 3: testing..." 75 numTests = 10; errorSum = 0.0; l = len(testx) 76 for j in xrange(numTests): 77 errorcount = 0.0 78 #print ‘the total number is: ‘,l 79 for i in xrange(l): 80 if logregress(testx[i], beta) != testy[i]: 81 errorcount += 1 82 #print "the number of error is: ", errorcount 83 print "the error rate is: ", (errorcount / l) 84 errorSum += (errorcount / l) 85 print "after %d iterations the average error rate is: %f" %(numTests, errorSum/numTests) 86 87 88 89 """ 90 trainx, trainy = loaddata(‘testSet‘) 91 print trainy 92 optimizaion(trainx, trainy) 93 """ 94 95 main() 96 97 print "cost time: ", (time.time() - st) 98 99 """ lineregres 100 # ssi = sigmod(zi) - sigmod(zi) ** 2 101 ss = [sigmodzi - sigmodzi ** 2 for sigmodzi in sigmodz] 102 # errssi = errori * ssi 103 errss = map(lambda x, y: x * y, error, ss) 104 # treri = errssi * trainxi(vector) 105 trer = [errss[i] * array(trainx[i]) for i in xrange(m)] 106 """
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原文地址:http://www.cnblogs.com/monne/p/4251804.html