Evaluation of the Classifiers in Multiparameter and Imbalanced Data Sets

被引:0
作者
Piotrowska, Ewelina [1 ]
机构
[1] Opole Univ Technol, Proszkowska 76 St, PL-45758 Opole, Poland
来源
INFORMATION SYSTEMS ARCHITECTURE AND TECHNOLOGY, ISAT 2019, PT II | 2020年 / 1051卷
关键词
Imbalanced data; Optimization methods; Classification;
D O I
10.1007/978-3-030-30604-5_24
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The paper discusses the basic problems resulting from the classification of imbalanced data, which are additionally described by a large number of parameters. The paper also presents various optimization methods, including the use of a synthetic indicator that is the product of specificity and the power of sensitivity, which was proposed by the author.
引用
收藏
页码:263 / 273
页数:11
相关论文
共 11 条
[1]  
ARMITAGE P, 1978, METODY STATYSTYCZNE
[2]  
Bator M., 2008, AUTOMATYCZNA DETEKCJ
[3]  
Chawla NV, 2010, DATA MINING AND KNOWLEDGE DISCOVERY HANDBOOK, SECOND EDITION, P875, DOI 10.1007/978-0-387-09823-4_45
[4]   Adaptive fraud detection [J].
Fawcett, T ;
Provost, F .
DATA MINING AND KNOWLEDGE DISCOVERY, 1997, 1 (03) :291-316
[5]  
Fernández A, 2011, LECT NOTES ARTIF INT, V6678, P1, DOI 10.1007/978-3-642-21219-2_1
[6]  
García V, 2010, LECT NOTES ARTIF INT, V6096, P541, DOI 10.1007/978-3-642-13022-9_54
[7]  
Gorecki H., 2006, OPTYMALIZACJA STEROW
[8]  
Japkowicz N, 1995, INT JOINT CONF ARTIF, P518
[9]   Machine learning for the detection of oil spills in satellite radar images [J].
Kubat, M ;
Holte, RC ;
Matwin, S .
MACHINE LEARNING, 1998, 30 (2-3) :195-215
[10]  
Piotrowska E, 2012, THESIS