Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 11
3237-3239,3285

Feature weighting scheme based on category information and term entropy

Alimjan Aysaa,b
Yin Xiaoyub
Kurban Ubulb
Li Zhea
a. Network & Information Technology Center, b. School of Information Science & Engineering, Xinjiang University, Urumqi 830046, China
DOI: 10.19734/j.issn.1001-3695.2018.05.0294

Abstract

Feature weighting schemes based on category information is not accurate enough to express the relationship between features and categories. That is the classification ability of the features with the same category frequency can't be compared, so the distribution of the features in the category should be considered. This paper combined the inverse category frequency(ICF) and inner category entropy of the features into the term weight calculation, and constructed two supervised feature weighting schemes. The experimental results on the Uygur text categorization dataset show that this method can obviously improve the spatial distribution of the samples and improve the micro average F1 value of the Uygur text classification.

Foundation Support

新疆维吾尔自治区自然科学基金资助项目(2016D01C068)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.05.0294
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 11
Section: Algorithm Research & Explore
Pages: 3237-3239,3285
Serial Number: 1001-3695(2019)11-007-3237-03

Publish History

[2019-11-05] Printed Article

Cite This Article

阿力木江·艾沙, 殷晓雨, 库尔班·吾布力, 等. 基于类别信息和特征熵的文本特征权重计算 [J]. 计算机应用研究, 2019, 36 (11): 3237-3239,3285. (Alimjan Aysa, Yin Xiaoyu, Kurban Ubul, et al. Feature weighting scheme based on category information and term entropy [J]. Application Research of Computers, 2019, 36 (11): 3237-3239,3285. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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