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根据SMO的算法描述，用python实现，部分代码如下，定义了一个svm_pmcp类，所有的运算在svm_pmcp完成，这样便于封装和实际应用

 

#!/usr/bin/env python# -*- coding: utf-8 -*-#麦好:myhaspl@qq.com#http://blog.csdn.net/u010255642#svm算法import numpy as np import mathimport matplotlib.pyplot as plt#内积线性核函数def arraydot(x,y):    return x.T*y#svm参数与计算类class svm_pmcp:    def __init__(self):        '''初始化参数变量'''        self.alpha = []        self.samples=[]        self.labels=[]        self.boundalpha=[]    def samples_init(self,samples):        '''样子及乘子参数初始化'''        for (mysp,mylb) in samples:            self.samples.append(mysp)            self.labels.append(mylb)        #初始化拉格朗日乘子alpha为0        for i in xrange(0,len(self.samples)):            self.alpha.append(0)        #初始化b为0        self.b = 0    def kernel_init(self,func):        '''指定核函数'''        self.kernel_func=func    def lagrange_multiplier(self,i):        '''求拉格朗日乘子'''        pass    def svmoutput(self,i):        pass    def tol_init(self,mytol):        self.tol=mytol    def eps_inbit(self,myeps):        self.eps=myeps    def c_init(selfm,myc):        self.c=myc    def choicesecond_max(self,nte):        pass    def choicesecond_random(self):        pass    def get_lh(self,i,j):        pass    def update_b(self):        pass    def update_w(self):        pass    def alpha_nozero_noc(self):        pass    def store_alpha(self,i1,a1,i2,a2):        pass    def takestep(i1,i2,e2,alpha2):        if (i1==i2):            return False        alpha1=lagrange_multiplier(i1)        y1=labels[i1]        e1=svmoutput(i1)-y1        s=y1*y2        l,h=get_lh(i2,i1)        if l==h:            return False        k11=kernel_func(self.samples[i1],self.samples[i1])        k12=kernel_func(self.samples[i1],self.samples[i2])        k13=kernel_func(self.samples[i2],self.samples[i2])        eta=float(2*k12-k11-k22)        if (eta<0):            a2=alpha2-y2*(e1-e2))/eta            if a2
    
     h:                a2=h        else:            lobj=obfuncl()            hobj=obfunch()            if lobj>hobj+self.eps:                a2=l            elif lobj
     
      self.tol and alpha2>0):             if (len(self.boundalpha)>0):                 myj=choicesecond_max(e)                 if takestep(myj,myi,e2,alpha2):                     return 1             else:                 myj=choicesecond_random(myi)                 if takestep(myj,myi,e2,alpha2):                     return 1        return 0        def loop1(self,nc):        for i in xrange(0,len(mysvm.samples)):            nc+=examineexample(i)    def loop2(self,nc):        for i in alpha_nozero_noc():            nc+=examineexample(i)    def mainroutine(self):        numchanged=0        examineall=True        while (numchanged>0 or examineall):            numchanged=0            if examineall:                numchanged=loop1(numchanged)            else:                numchanged=loop2(numchanged)            examineall=not examinealldef mainsvm(mysamples):    mysvm = svm_pmcp()    mysvm.samples_init(mysamples)    mysvm.kernel_init(arraydot)    mysvm.tol_init(0.001)    mysvm.eps_init(0.00001)    mysvm.c_init(1)    mysvm.mainroutine()
     
    

后面关于svm的章节将提供类下载地址及调用代码