01、 使用Naive Bayes分类器的classify-sklearn算法在16S rRNA基因和真菌ITS序列物种注释的精确度和严谨性方面优于其他的标准分类方法,可以最大程度上确保注释结果的可靠、准确。通过建立基于人工群落(mock community)、交叉验证(cross-validated)和新物种检出(novel taxa evaluations)的三维评价模型,可以发现classify-sklea...
# 需要导入模块: from nltk.classify.scikitlearn import SklearnClassifier [as 别名]# 或者: from nltk.classify.scikitlearn.SklearnClassifier importbatch_classify[as 别名]classSVMTweetClassifier(TweetClassifier):""" A simple Naive Bayes classifier. Documents are tokenized and stemmed, and then...
# 需要导入模块: from nltk.classify.scikitlearn import SklearnClassifier [as 别名]# 或者: from nltk.classify.scikitlearn.SklearnClassifier importprob_classify[as 别名]print"creating feature sets..."tweetlist = tweetTest.loadTwitterCSV('trainingandtestdata/testdata.csv') labeld_features = ...
average_Precision = dict()fortraincv, testcvincv:#BasedNaiveClassifierBasedNaiveClassifier = NaiveBayesClassifier.train(training[traincv[0]:traincv[len(traincv)-1]]) accuracy = (nltk.classify.util.accuracy(BasedNaiveClassifier, training[testcv[0]:testcv[len(testcv)-1]]))*100Naive_Accu += a...