docList.append(wordList) classList.append(0) except: continue else: pass vocaList = NaiveBayes.createVocabList(docList) trainMat = [] for postinDoc in docList: trainMat.append(NaiveBayes.setOfWords2Vec(vocaList, postinDoc)) print('vocaList : ', vocaList) print('trainMat : ', trainMat) print('testEntry : ', testEntry) p0V, p1V, pAb = NaiveBayes.trainNB0(array(trainMat), array(classList)) # testEntry = ['카카오', '인공지능', '알파고'] thisDoc = array(NaiveBayes.setOfWords2Vec(vocaList, testEntry)) print(testIssueDate, ' 일자의 ', testTitle, '기사 이후 주가는 ?\n', NaiveBayes.classifyNB(thisDoc, p0V, p1V, pAb)) else: print("Error Code:" + rescode)