Feature selection based on similarity

被引：6
|
作者：
Lazzerini, B [1 ]
Marcelloni, F [1 ]
机构：
[1] Univ Pisa, Dipartimento Ingn Informaz, I-56122 Pisa, Italy
来源：
ELECTRONICS LETTERS | 2002年 / 38卷 / 03期
关键词：
D O I：
10.1049/el:20020078
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A new method for feature selection is proposed. The method associates a weight with each feature by minimising an appropriate index defined in terms of similarity between patterns of the training set. The weight measures the importance of the corresponding feature in characterising the classes. Features associated with low weights are considered irrelevant and therefore eliminated. Experimental results to confirm the validity of the method are shown.
引用
收藏
页码：121 / 122
页数：2
相关论文
共 50 条
  • [41] A Study of Image Retrieval System Based on Feature Extraction, Selection, Classification and Similarity Measurements
    Yogapriya, J.
    Saravanabhavan, C.
    Asokan, R.
    Vennila, Ila.
    Preethi, P.
    Nithya, B.
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2018, 8 (03) : 479 - 484
  • [42] A study on similarity measures for the feature selection method OFFSS
    Rong, JG
    Wang, XZ
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 1869 - 1873
  • [43] Similarity Searching for Potent Compounds Using Feature Selection
    Vogt, Martin
    Bajorath, Juergen
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2013, 53 (07) : 1613 - 1619
  • [44] Subspace clustering by simultaneously feature selection and similarity learning
    Zhong, Guo
    Pun, Chi-Man
    KNOWLEDGE-BASED SYSTEMS, 2020, 193
  • [45] Improved Feature Selection by Incorporating Gene Similarity into the LASSO
    Gillies, C. E.
    Gao, X.
    Patel, N. V.
    Siadat, M-R.
    Wilson, G. D.
    12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), 2012, : 41 - 48
  • [46] Information Theory-Based Feature Selection: Minimum Distribution Similarity with Removed Redundancy
    Zhang, Yu
    Lin, Zhuoyi
    Kwoh, Chee Keong
    COMPUTATIONAL SCIENCE - ICCS 2020, PT V, 2020, 12141 : 3 - 17
  • [47] MUSIPER: a system for modeling music similarity perception based on objective feature subset selection
    Sotiropoulos, Dionysios N.
    Lampropoulos, Aristomenis S.
    Tsihrintzis, George A.
    USER MODELING AND USER-ADAPTED INTERACTION, 2008, 18 (04) : 315 - 348
  • [48] Unsupervised feature selection method based on iterative similarity graph factorization and clustering by modularity
    Oliveira, Marcos de S.
    Queiroz, Sergio R. de M.
    de Carvalho, Francisco de A. T.
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 208
  • [49] MUSIPER: a system for modeling music similarity perception based on objective feature subset selection
    Dionysios N. Sotiropoulos
    Aristomenis S. Lampropoulos
    George A. Tsihrintzis
    User Modeling and User-Adapted Interaction, 2008, 18 : 315 - 348
  • [50] Unsupervised similarity-based feature selection using heuristic Hopfield neural networks
    Shi, SYM
    Suganthan, PN
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4, 2003, : 1838 - 1843
12345