Efficient feature selection for logical analysis of large-scale multi-class datasets

被引：3

作者：

Yan, Kedong ^{[1
]}

Miao, Dongjing ^{[2
]}

Guo, Cui ^{[3
]}

Huang, Chanying ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, 200 Xiaolingwei, Nanjing 210094, Peoples R China

[2] Harbin Inst Technol, Fac Comp, 92 Xidazhi, Harbin 150001, Peoples R China

[3] Shantou Univ, Business Sch, 243 Daxue Rd, Shantou 515063, Peoples R China

来源：

JOURNAL OF COMBINATORIAL OPTIMIZATION | 2021年 / 42卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Logical Analysis of Data; Supervised Learning; Feature Selection; Multi-classification; Set Covering;

D O I：

10.1007/s10878-021-00732-2

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Feature selection in logical analysis of data (LAD) can be cast into a set covering problem. In this paper, extending the results on feature selection for binary classification using LAD, we present a mathematical model that selects a minimum set of necessary features for multi-class datasets and develop a heuristic algorithm that is both memory and time efficient for this model correspondingly. The utility of the algorithm is illustrated on a small example and the superiority of our work is demonstrated through experiments on 6 real-life multi-class datasets from UCI repository.

引用

页码：1 / 23

页数：23

共 50 条

[11] Dynamic ensemble selection for multi-class imbalanced datasets
Garcia, Salvador
Zhang, Zhong-Liang
Altalhi, Abdulrahman
Alshomrani, Saleh
Herrera, Francisco
INFORMATION SCIENCES, 2018, 445 : 22 - 37
[12] Feature selection with multi-class logistic regression
Wang, Jingyu
Wang, Hongmei
Nie, Feiping
Li, Xuelong
NEUROCOMPUTING, 2023, 543
[13] Scalable Feature Selection for Multi-class Problems
Chidlovskii, Boris
Lecerf, Loic
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PART I, PROCEEDINGS, 2008, 5211 : 227 - 240
[14] Multi-class feature selection for texture classification
Chen, Xue-wen
Zeng, Xiangyan
van Alphen, Deborah
PATTERN RECOGNITION LETTERS, 2006, 27 (14) : 1685 - 1691
[15] Feature selection and its combination with data over-sampling for multi-class imbalanced datasets
Tsai, Chih-Fong
Chen, Kuan-Chen
Lin, Wei -Chao
APPLIED SOFT COMPUTING, 2024, 153
[16] Feature Selection Based on Kernel Discriminant Analysis for Multi-Class Problems
Ishii, Tsuneyoshi
Abe, Shigeo
2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 2455 - 2460
[17] Local Feature Selection by Formal Concept Analysis for Multi-class Classification
Ikeda, Madori
Yamamoto, Akihiro
TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING, 2014, 8643 : 470 - 482
[18] Multi-class feature selection by exploring reliable class correlation
Wang, Zhenyu
Wang, Chenchen
Wei, Jinmao
Liu, Jian
KNOWLEDGE-BASED SYSTEMS, 2021, 230
[19] Efficient Decomposition Selection for Multi-class Classification
Chen, Yawen
Wen, Zeyi
He, Bingsheng
Chen, Jian
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 35 (04) : 3751 - 3764
[20] Effective Feature Selection for Multi-class Classification Models
Lin, Hung-Yi
WORLD CONGRESS ON ENGINEERING - WCE 2013, VOL III, 2013, : 1474 - 1479

← 1 2 3 4 5 →