def tests(): bayes.testingNB() bayes.spamTest()
# -*- coding: UTF-8 -*- 或者 #coding=utf-8 ''' Created on 2016年8月20日 @author: xiaoyuan ''' import bayes bayes.testingNB()
listOPosts, listClasses = bayes.loadDataSet() myVocabList = bayes.createVocabList(listOPosts) print myVocabList print bayes.setOfWords2Vec(myVocabList, listOPosts[0]) print bayes.setOfWords2Vec(myVocabList, listOPosts[3]) trainMat = [] for postinDoc in listOPosts: trainMat.append(bayes.setOfWords2Vec(myVocabList, postinDoc)) p0V, p1V, pAb = bayes.trainNB0(trainMat, listClasses) print pAb print p0V print p1V bayes.testingNB() print '==email classify==' bayes.spamTest() print '==email classify==' bayes.spamTest() print '==email classify==' bayes.spamTest() print '==feedparser classify==' ny = feedparser.parse('http://newyork.craigslist.org/stp/index.rss') sf = feedparser.parse('http://sfbay.craigslist.org/stp/index.rss') vocabList, pSF, pNY = bayes.localWords(ny, sf) vocabList, pSF, pNY = bayes.localWords(ny, sf) bayes.getTopWords(ny, sf)
def test_nb(self): bayes.testingNB()
import bayes from numpy import * listOPosts, listClasses = bayes.loadDataSet() # print(listOPosts) myVocalList = bayes.createVocabList(listOPosts) # print(myVocalList) # # print(bayes.setOfwords2Vec(myVocalList,listOPosts[0])) # trainMat=[] # for postinDoc in listOPosts: # trainMat.append(bayes.setOfwords2Vec(myVocalList,postinDoc)) # p0V,p1V,pAb=bayes.trainNB0(trainMat,listClasses) # print(pAb,p0V,p1V) print(bayes.testingNB())
# -*- coding:utf-8 -*- import bayes print bayes.testingNB()