def getTrainAdaboostInfo():
"""
获取训练算法阶段的DS和minErrorRate信息
:return:
"""
trainDS = np.loadtxt('trainDS.txt', delimiter='\t')
trainMinErrorRate = np.loadtxt('trainMinErrorRate.txt', delimiter='\t')
vocabularyList = boostNaiveBayes.getVocabularyList('vocabularyList.txt')
pWordsSpamicity = np.loadtxt('pWordsSpamicity.txt', delimiter='\t')
pWordsHealthy = np.loadtxt('pWordsHealthy.txt', delimiter='\t')
pSpam = np.loadtxt('pSpam.txt', delimiter='\t')
return vocabularyList, pWordsSpamicity, pWordsHealthy, pSpam, trainMinErrorRate, trainDS
def getTrainAdaboostInfo():
"""
获取训练算法阶段的DS和minErrorRate信息
:return:
"""
trainDS = np.loadtxt('trainDS.txt', delimiter='\t')
trainMinErrorRate = np.loadtxt('trainMinErrorRate.txt', delimiter='\t')
vocabularyList = boostNaiveBayes.getVocabularyList('vocabularyList.txt')
pWordsSpamicity = np.loadtxt('pWordsSpamicity.txt', delimiter='\t')
pWordsHealthy = np.loadtxt('pWordsHealthy.txt', delimiter='\t')
pSpam = np.loadtxt('pSpam.txt', delimiter='\t')
return vocabularyList, pWordsSpamicity, pWordsHealthy, pSpam, trainMinErrorRate, trainDS
