Generally, NLTK is used primarily for general NLP tasks (tokenization, POS tagging, parsing, etc.) Sklearn is used primarily for machine learning (classification, clustering, etc.) Gensim is used primarily for topic modeling and document similarity.…
Bag-of-words Model Previous state-of-the-art document representations were based on the bag-of-words model, which represent input documents as a fixed-length vector. For example, borrowing from the Wikipedia article, the two documents(1) John likes t…
1.基于词袋模型的逻辑回归情感分类 # coding: utf-8 import re import numpy as np import pandas as pd from bs4 import BeautifulSoup from sklearn.feature_extraction.text import CountVectorizer from sklearn.metrics import confusion_matrix from sklearn.linear_model import…
我有两个目录,我想从中读取它们的文本文件并给它们贴上标签,但我不知道如何通过taggedDocument来实现这一点.我以为它可以作为标记文档([strings],[labels])工作,但这显然不起作用. from gensim import models from gensim.models.doc2vec import TaggedDocument import utilities as util import os from sklearn import svm from nltk.to…
https://www.pythonprogramming.net/words-as-features-nltk-tutorial/ Converting words to Features with NLTK In this tutorial, we're going to be building off the previous video and compiling feature lists of words from positive reviews and words from th…
QQ:231469242 欢迎喜欢nltk朋友交流 https://www.pythonprogramming.net/text-classification-nltk-tutorial/?completed=/wordnet-nltk-tutorial/ Text Classification with NLTK Now that we're comfortable with NLTK, let's try to tackle text classification. The goal wit…
QQ:231469242 欢迎nltk爱好者交流 https://www.pythonprogramming.net/named-entity-recognition-nltk-tutorial/?completed=/chinking-nltk-tutorial/ Named Entity Recognition with NLTK 命名实体(Named Entity)类别识别 This is a temporary script file. """ import nltk…
https://www.pythonprogramming.net/chinking-nltk-tutorial/?completed=/chunking-nltk-tutorial/ 代码 # -*- coding: utf-8 -*- """ Created on Sun Nov 13 09:14:13 2016 @author: daxiong """ import nltk from nltk.corpus import state_un…