3
다음 코드에서, naivebayes 분류기가 trainset1에서 올바르게 작동하지만 trainset2에서 작동하지 않는 이유는 무엇인지 정확하게 알고 있습니다. TextBlob과 nltk의 두 분류 자에 대해서도 시도해 보았습니다.nltk naivebayes 텍스트 분류를위한 분류 자
from textblob.classifiers import NaiveBayesClassifier
from textblob import TextBlob
from nltk.tokenize import word_tokenize
import nltk
trainset1 = [('I love this sandwich.', 'pos'),
('This is an amazing place!', 'pos'),
('I feel very good about these beers.', 'pos'),
('This is my best work.', 'pos'),
("What an awesome view", 'pos'),
('I do not like this restaurant', 'neg'),
('I am tired of this stuff.', 'neg'),
("I can't deal with this", 'neg'),
('He is my sworn enemy!', 'neg'),
('My boss is horrible.', 'neg')]
trainset2 = [('hide all brazil and everything plan limps to anniversary inflation plan initiallyis limping its first anniversary amid soaring prices', 'class1'),
('hello i was there and no one came', 'class2'),
('all negative terms like sad angry etc', 'class2')]
def nltk_naivebayes(trainset, test_sentence):
all_words = set(word.lower() for passage in trainset for word in word_tokenize(passage[0]))
t = [({word: (word in word_tokenize(x[0])) for word in all_words}, x[1]) for x in trainset]
classifier = nltk.NaiveBayesClassifier.train(t)
test_sent_features = {word.lower(): (word in word_tokenize(test_sentence.lower())) for word in all_words}
return classifier.classify(test_sent_features)
def textblob_naivebayes(trainset, test_sentence):
cl = NaiveBayesClassifier(trainset)
blob = TextBlob(test_sentence,classifier=cl)
return blob.classify()
test_sentence1 = "he is my horrible enemy"
test_sentence2 = "inflation soaring limps to anniversary"
print nltk_naivebayes(trainset1, test_sentence1)
print nltk_naivebayes(trainset2, test_sentence2)
print textblob_naivebayes(trainset1, test_sentence1)
print textblob_naivebayes(trainset2, test_sentence2)
출력 :
neg
class2
neg
class2
test_sentence2 명확하게 CLASS1에 속해 있지만.