Dataset：fetch_20newsgroups(20类新闻文本)数据集的简介、安装、使用方法之详细攻略
目录
fetch_20newsgroups(20类新闻文本)数据集的简介
1、数据集信息
2、数据集标签20类别
3、数据集前三篇文章
fetch_20newsgroups(20类新闻文本)数据集的安装
fetch_20newsgroups(20类新闻文本)数据集的使用方法
fetch_20newsgroups(20类新闻文本)数据集的简介20 newsgroups数据集18000多篇新闻文章，一共涉及到20种话题，所以称作20newsgroups text dataset，分为两部分：训练集和测试集，通常用来做文本分类，均匀分为20个不同主题的新闻组集合。20newsgroups数据集是被用于文本分类、文本挖据和信息检索研究的国际标准数据集之一。一些新闻组的主题特别相似(e.g. comp.sys.ibm.pc.hardware/ comp.sys.mac.hardware)，还有一些却完全不相关 (e.g misc.forsale /soc.religion.christian)。
1、数据集信息数据集形状 (18846,)
================= ========== Classes 20 Samples total 18846 Dimensionality 1 Features text ================= ==========
2、数据集标签20类别['alt.atheism', 'comp.graphics', 'comp.os.ms-windows.misc', 'comp.sys.ibm.pc.hardware', 'comp.sys.mac.hardware', 'comp.windows.x', 'misc.forsale', 'rec.autos', 'rec.motorcycles', 'rec.sport.baseball', 'rec.sport.hockey', 'sci.crypt', 'sci.electronics', 'sci.med', 'sci.space', 'soc.religion.christian', 'talk.politics.guns', 'talk.politics.mideast', 'talk.politics.misc', 'talk.religion.misc']
3、数据集前三篇文章["From: Mamatha Devineni Ratnam \nSubject: Pens fans reactions\nOrganization: Post Office, Carnegie Mellon, Pittsburgh, PA\nLines: 12\nNNTP-Posting-Host: po4.andrew.cmu.edu\n\n\n\nI am sure some bashers of Pens fans are pretty confused about the lack\nof any kind of posts about the recent Pens massacre of the Devils. Actually,\nI am bit puzzled too and a bit relieved. However, I am going to put an end\nto non-PIttsburghers' relief with a bit of praise for the Pens. Man, they\nare killing those Devils worse than I thought. Jagr just showed you why\nhe is much better than his regular season stats. He is also a lot\nfo fun to watch in the playoffs. Bowman should let JAgr have a lot of\nfun in the next couple of games since the Pens are going to beat the pulp out of Jersey anyway. I was very disappointed not to see the Islanders lose the final\nregular season game. PENS RULE!!!\n\n", 'From: mblawson@midway.ecn.uoknor.edu (Matthew B Lawson)\nSubject: Which high-performance VLB video card?\nSummary: Seek recommendations for VLB video card\nNntp-Posting-Host: midway.ecn.uoknor.edu\nOrganization: Engineering Computer Network, University of Oklahoma, Norman, OK, USA\nKeywords: orchid, stealth, vlb\nLines: 21\n\n My brother is in the market for a high-performance video card that supports\nVESA local bus with 1-2MB RAM. Does anyone have suggestions/ideas on:\n\n - Diamond Stealth Pro Local Bus\n\n - Orchid Farenheit 1280\n\n - ATI Graphics Ultra Pro\n\n - Any other high-performance VLB card\n\n\nPlease post or email. Thank you!\n\n - Matt\n\n-- \n | Matthew B. Lawson (mblawson@essex.ecn.uoknor.edu) | \n --+-- "Now I, Nebuchadnezzar, praise and exalt and glorify the King --+-- \n | of heaven, because everything he does is right and all his ways | \n | are just." - Nebuchadnezzar, king of Babylon, 562 B.C. | \n']
fetch_20newsgroups(20类新闻文本)数据集的安装手动下载地址：https://people.csail.mit.edu/jrennie/20Newsgroups/20news-bydate.tar.gz
fetch_20newsgroups(data_home=None, # 文件下载的路径
subset='train', # 加载那一部分数据集 train/test
categories=None, # 选取哪一类数据集[类别列表]，默认20类
shuffle=True, # 将数据集随机排序
random_state=42, # 随机数生成器
remove=(), # ('headers','footers','quotes') 去除部分文本
download_if_missing=True # 如果没有下载过，重新下载
)
news = fetch_20newsgroups(subset='all')ML之LoR：利用pipeline对fetch_20newsgroups数据集(文本抽取TfidfVectorizer)采用SVC算法(GSCV)实现多分类ML之NB：利用朴素贝叶斯NB算法(CountVectorizer+不去除停用词)对fetch_20newsgroups数据集(20类新闻文本)进行分类预测、评估
