Correction to: An empirical study on the joint impact of feature selection and data resampling on imbalance classification

被引：0
|
作者：
Chongsheng Zhang
Paolo Soda
Jingjun Bi
Gaojuan Fan
George Almpanidis
Salvador García
Weiping Ding
机构：
[1] Henan University,Henan Key Lab of Big Data Analysis and Processing
[2] University Campus Bio-Medico of Rome,Department of Engineering
[3] Umea University,Department of Radiation Sciences, Radiation Physics, Biomedical Engineering
[4] University of Granada,DaSCI Andalusian Research Institute
[5] Nantong University,School of Information Science and Technology
来源：
Applied Intelligence | 2023年 / 53卷
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：8506 / 8506
相关论文
共 50 条
  • [1] An empirical study on the joint impact of feature selection and data resampling on imbalance classification
    Zhang, Chongsheng
    Soda, Paolo
    Bi, Jingjun
    Fan, Gaojuan
    Almpanidis, George
    Garcia, Salvador
    Ding, Weiping
    APPLIED INTELLIGENCE, 2023, 53 (05) : 5449 - 5461
  • [2] An empirical study on the joint impact of feature selection and data resampling on imbalance classification
    Chongsheng Zhang
    Paolo Soda
    Jingjun Bi
    Gaojuan Fan
    George Almpanidis
    Salvador García
    Weiping Ding
    Applied Intelligence, 2023, 53 : 5449 - 5461
  • [3] An empirical study on the joint impact of feature selection and data resampling on imbalance classification (Jun, 10.1007/s10489-022-03772-1, 2022)
    Zhang, Chongsheng
    Soda, Paolo
    Bi, Jingjun
    Fan, Gaojuan
    Almpanidis, George
    Garcia, Salvador
    Ding, Weiping
    APPLIED INTELLIGENCE, 2023, 53 (07) : 8506 - 8506
  • [4] Feature Selection and Resampling in Class Imbalance Learning: Which Comes First? An Empirical Study in the Biological Domain
    Zhang, Chongsheng
    Bi, Jingjun
    Soda, Paolo
    2017 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2017, : 933 - 938
  • [5] An Approach Based on Resampling and Feature Selection to Improve the Classification of Microarray Data
    Soleymani, Nafiseh
    Moattar, Mohammad Hussein
    2018 6TH IRANIAN JOINT CONGRESS ON FUZZY AND INTELLIGENT SYSTEMS (CFIS), 2018, : 61 - 64
  • [6] Comprehensive empirical investigation for prioritizing the pipeline of using feature selection and data resampling techniques
    Tyagi, Pooja
    Singh, Jaspreeti
    Gosain, Anjana
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (03) : 6019 - 6040
  • [7] Feature selection in imbalance data sets
    Jamali, Ilnaz
    Bazmara, Mohammad
    Jafari, Shahram
    International Journal of Computer Science Issues, 2012, 9 (3 3-2): : 42 - 45
  • [8] Similarity of feature selection methods: An empirical study across data intensive classification tasks
    Dessi, Nicoletta
    Pes, Barbara
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (10) : 4632 - 4642
  • [9] Impact of feature selection methods on data classification for IDS
    Jiang, Shuai
    Xu, Xiaolong
    2019 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC), 2019, : 174 - 180
  • [10] Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data
    Nieto-del-Amor, Felix
    Prats-Boluda, Gema
    Garcia-Casado, Javier
    Diaz-Martinez, Alba
    Jose Diago-Almela, Vicente
    Monfort-Ortiz, Rogelio
    Hao, Dongmei
    Ye-Lin, Yiyao
    SENSORS, 2022, 22 (14)
12345