SMO序列最小最优化算法

时间:2023-03-09 05:35:18
SMO序列最小最优化算法

SMO序列最小最优化算法

SMO例子:

SMO序列最小最优化算法
  1 from numpy import *
2 import matplotlib
3 import matplotlib.pyplot as plt
4
5 def loadDataSet(fileName):
6 dataMat = []; labelMat = []
7 fr = open(fileName)
8 for line in fr.readlines():
9 lineArr = line.strip().split(',')
10 dataMat.append([float(lineArr[0]), float(lineArr[1])])
11 labelMat.append(float(lineArr[2]))
12 return dataMat, labelMat
13
14 def selectJrand(i, m):
15 j = i
16 while (j == i):
17 j = int(random.uniform(0, m))
18 return j
19
20 def clipAlpha(aj, H, L):
21 if aj > H:
22 aj = H
23 if L > aj:
24 aj = L
25 return aj
26
27
28 def smoSimple(dataMatIn, classLabels, C, toler, maxIter):
29 dataMatrix = mat(dataMatIn); labelMat = mat(classLabels).transpose()
30 b = 0; m, n = shape(dataMatrix)
31 alphas = mat(zeros((m, 1)))
32 iter = 0
33 while (iter < maxIter):
34 alphaPairsChanged = 0 #用于记录alpha是否已经进行优化
35 for i in range(m):
36 fXi = float(multiply(alphas, labelMat).T*(dataMatrix*dataMatrix[i,:].T))+b # 预测的类别
37 Ei = fXi - float(labelMat[i]) #实际结果与真实结果的误差,如果误差很大,那么就要对该数据实例所对应的alpha值进行优化
38 if ((labelMat[i]*Ei < -toler) and (alphas[i] < C)) or ((labelMat[i]*Ei > toler) and (alphas[i]>0)):
39 j = selectJrand(i, m)
40 fXj = float(multiply(alphas, labelMat).T*(dataMatrix*dataMatrix[j, :].T))+b
41 Ej = fXj - float(labelMat[j])
42 alphaIold = alphas[i].copy()
43 alphaJold = alphas[j].copy()
44 if (labelMat[i] != labelMat[j]):
45 L = max(0, alphas[j] - alphas[i])
46 H = min(C, C+alphas[j]-alphas[i])
47 else:
48 L = max(0, alphas[j]+alphas[i]-C)
49 H = min(C, alphas[j]+alphas[i])
50 if L == H: print("L == H"); continue
51 eta = 2.0 * dataMatrix[i, :]*dataMatrix[j,:].T-dataMatrix[i,:]*dataMatrix[i,:].T-dataMatrix[j,:]*dataMatrix[j,:].T
52 if eta >= 0: print("eta >= 0"); continue
53 alphas[j] -= labelMat[j]*(Ei-Ej)/eta
54 alphas[j] = clipAlpha(alphas[j], H, L)
55 if (abs(alphas[j] - alphaJold) < 0.00001): print("j not moving enough"); continue
56 alphas[i] += labelMat[j] * labelMat[i] * (alphaJold-alphas[j])
57 b1 = b - Ei - labelMat[i]*(alphas[i]-alphaIold)*dataMatrix[i,:]*dataMatrix[i,:].T-labelMat[j]*(alphas[j]-alphaJold)*dataMatrix[i,:]*dataMatrix[j,:].T
58 b2 = b - Ej - labelMat[i]*(alphas[i]-alphaIold)*dataMatrix[i,:]*dataMatrix[j,:].T-labelMat[j]*(alphas[j]-alphaJold)*dataMatrix[j,:]*dataMatrix[j,:].T
59 if (0 < alphas[i]) and (C > alphas[i]): b = b1
60 elif (0 < alphas[j]) and (C > alphas[j]): b = b2
61 else: b = (b1+b2)/2.0
62 alphaPairsChanged += 1
63 print("iter: %d i:%d, pairs changed %d" % (iter, i, alphaPairsChanged))
64 if (alphaPairsChanged == 0): iter += 1
65 else: iter = 0
66 print("iteration number: %d" % iter)
67 return b, alphas
68
69 def draw(alpha, bet, data, label):
70 plt.xlabel(u"x1")
71 plt.xlim(0, 100)
72 plt.ylabel(u"x2")
73 for i in range(len(label)):
74 if label[i] > 0:
75 plt.plot(data[i][0], data[i][1], 'or')
76 else:
77 plt.plot(data[i][0], data[i][1], 'og')
78 w1 = 0.0
79 w2 = 0.0
80 for i in range(len(label)):
81 w1 += alpha[i] * label[i] * data[i][0]
82 w2 += alpha[i] * label[i] * data[i][1]
83 w = float(- w1 / w2)
84
85 b = float(- bet / w2)
86 r = float(1 / w2)
87 lp_x1 = list([10, 90])
88 lp_x2 = []
89 lp_x2up = []
90 lp_x2down = []
91 for x1 in lp_x1:
92 lp_x2.append(w * x1 + b)
93 lp_x2up.append(w * x1 + b + r)
94 lp_x2down.append(w * x1 + b - r)
95 lp_x2 = list(lp_x2)
96 lp_x2up = list(lp_x2up)
97 lp_x2down = list(lp_x2down)
98 plt.plot(lp_x1, lp_x2, 'b')
99 plt.plot(lp_x1, lp_x2up, 'b--')
100 plt.plot(lp_x1, lp_x2down, 'b--')
101 plt.show()
102
103
104
105 filestr = "E:\\Kaggle\\Digit Recognizer\\svmtest.txt"
106
107 dataArr, labelArr = loadDataSet(filestr)
108 print(dataArr)
109 print(labelArr)
110 b, alphas = smoSimple(dataArr, labelArr, 0.6, 0.001, 40);
111 print(b)
112 print(alphas)
113 draw(alphas, b, dataArr, labelArr)
SMO序列最小最优化算法

下面是测试集

SMO序列最小最优化算法
 1 27,53,-1
2 49,37,-1
3 56,39,-1
4 28,60,-1
5 68,75,1
6 57,69,1
7 64,62,1
8 77,68,1
9 70,54,1
10 56,63,1
11 25,41,-1
12 66,34,1
13 55,79,1
14 77,31,-1
15 46,66,1
16 30,23,-1
17 21,45,-1
18 68,42,-1
19 43,43,-1
20 56,59,1
21 79,68,1
22 60,34,-1
23 49,32,-1
24 80,79,1
25 77,46,1
26 26,66,1
27 29,29,-1
28 77,34,1
29 20,71,-1
30 49,25,-1
31 58,65,1
32 33,57,-1
33 31,79,1
34 20,78,1
35 77,37,-1
36 73,34,-1
37 60,26,-1
38 77,66,1
39 71,75,1
40 35,36,-1
41 49,61,1
42 26,37,-1
43 42,73,1
44 36,50,-1
45 66,73,1
46 71,43,1
47 33,62,1
48 43,41,-1
49 42,29,-1
50 58,20,-1
SMO序列最小最优化算法

下面是结果:

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" alt="" />

以上推导内容转自:http://liuhongjiang.github.io/tech/blog/2012/12/28/svm-smo/