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