问题描述
我想创建自己的简单特征选择算法。该数据集,我要一起工作是这里 (非常著名的数据集)。有人可以给我如何做到这一点的指针?
I am trying to create my own and simple feature selection algorithm. The data set that I am going to work with is here (very famous data set). Can someone give me a pointer on how to do so?
我打算写一个特点排名算法的文本分类。这是电影审查的情感分析,将之列为无论是积极的还是消极的。
I am planning to write a feature rank algorithm for a text classification. This is for a sentiment analysis of movie reviews, classifying them as either positive or negative.
所以我的问题是关于如何编写一个文本数据集的简单特征选择。
So my question is on how to write a simple feature selection for a text data set.
推荐答案
特征选择方法是一个很大的话题。你可以用下面的启动:
Feature selection methods are a big topic. You can start with following:
-
卡方
Chi square
互信息
词频
等。阅读本文,如果你有时间:在特征选择比较研究文本分类这将帮助你很多。
etc. Read this paper if you have time: Comparative study on feature selection in text categorization this will help you lot.
的实际实现取决于你如何pre-过程中的数据。基本上,它保持计数,无论是哈希表或数据库。
The actual implementation depends on how you pre-process the data. Basically its keeping the counts, be it hash table or a database.
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