NameError异常怎么处理？

Question

# coding=utf-8  from numpy import *def loadDataSet():        postingList = [['my', 'dog', 'has', 'flea', 'problems', 'help', 'please'],        ['maybe', 'not', 'take', 'him', 'to', 'dog', 'park', 'stupid'],       ['my', 'dalmation', 'is', 'so', 'cute', 'I', 'love', 'him'],       ['stop', 'posting', 'stupid', 'worthless', 'garbage'],        ['mr', 'licks', 'ate', 'my', 'steak', 'how', 'to', 'stop', 'him'],       ['quit', 'buying', 'worthless', 'dog', 'food', 'stupid']]        classVec = [0, 1, 0, 1, 0, 1]  # 1代表侮辱性文字，0代表正常言论       return postingList, classVec       def createVocabList(dataSet):       vocabSet = set([])        for document in dataSet:            vocabSet = vocabSet | set(document)       return list(vocabSet)       def setOfWords2Vec(vocabList, inputSet):       returnVec = [0] * len(vocabList)       for word in inputSet:           if word in vocabList:                returnVec[vocabList.index(word)] = 1           else:print "the word: %s is not in my Vocabulary!" % word       return returnVec  def trainNB0(trainMatrix, trainCategory):       numTrainDocs = len(trainMatrix)    numWords = len(trainMatrix[0])        pAbusive = sum(trainCategory) / float(numTrainDocs)      p0Num = zeros(numWords); p1Num = zeros(numWords)       p0Denom = 0.0; p1Denom = 0.0     for i in range(numTrainDocs):           if trainCategory[i] == 1:               p1Num += trainMatrix[i]                p1Denom += sum(trainMatrix[i])           else:                p0Num += trainMatrix[i]                p0Denom += sum(trainMatrix[i])       p1Vect = p1Num / p1Denom    p0Vect = p0Num / p0Denom     return p0Vect, p1Vect, pAbusive

Answer 1

报错很明显啊，你的bayes变量没有定义