However, a comparative experimental study on redundant feature selection methods in the field of text mining has not been reported yet. In order to solve this problem, an extensive empirical comparative study with the task of text classification is given in the paper. The experimental results ...
In text classification, the feature selection is the process of selecting a specific subset of the terms of the training set and using only them in the classification algorithm. The feature selection process takes place before the training of the classifier. Update: The Datumbox Machine Learning Fr...
Feature selection is the key issue in text classification because there are a large number of attributes.In this paper,we propose a new algorithm OR+SVM-RFE that integrates Odds Radio(OR) with recursive feature elimination based on SVM(SVM-RFE).Odds Radio is first used to roughly and rapidly...
A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification Owing to its openness, virtualization and sharing criterion, the Internet has been rapidly becoming a platform for people to express their opinion, attitud... Suge Wang a b,Deyu Li b c,Xiaolei Song...
Feature selection for text classification with Naïve Bayes As an important preprocessing technology in text classification, feature selection can improve the scalability, efficiency and accuracy of a text classifie... Jingnian,Chen,and,... - 《Expert Systems with Applications》 被引量: 365发表: ...
with many feature selection techniques and K-Nearest Neighbor classifier works well only in the cases, when the feature selection techniques either Information Gain (IG) or Mutual Information (MI). To improve the accuracy of long text classification of Chinese news, Chen et al.26 propose a BERT...
The recently introduced Gini-Index Text (GIT) feature-selection algorithm for text classification, through incorporating an improved Gini Index for better feature-selection performance, has some drawbacks. Specifically, the algorithm, under real-world experimental conditions, concentrates feature values to ...
特征选择 (feature_selection) [toc] 本文主要参考sklearn(0.18版为主,部分0.17)的1.13节的官方文档,以及一些工程实践整理而成。 当数据预处理完成后,我们需要选择有意义的特征输入机器学习的算法和模型进行训练。通常来说,从两个方面考虑来选择特征: 特征是否发散
特征选择 (feature_selection) 目录 特征选择 (feature_selection) Filter 1. 移除低方差的特征 (Removing features with low variance) 2. 单变量特征选择 (Univariate feature selection
Especially in unbalanced text, where the number of training documents between each category is unbalanced,it needs proper feature selection method tha... M Widiasri,A Justitia 被引量: 0发表: 2013年 Gini-index Based and Local Class Central Vector Weighted kNN Classification Algorithm As a simple,...