A Review of Classification Algorithms for Data Mining

被引:3
作者
Li Mindong [1 ]
Chen Qingwei [1 ]
Huang Panling [1 ]
Zhou Jun [1 ]
Gong Weike [2 ]
机构
[1] Shandong Univ, Jinan, Shandong, Peoples R China
[2] Shandong Bosheng Power Technol CO LTD, Linyi, Shandong, Peoples R China
来源
2019 2ND INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC AND ENGINEERING TECHNOLOGY (MEET 2019) | 2019年
关键词
data mining; classification algorithm; review;
D O I
10.23977/meet.2019.93758
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
Classification algorithm is one of the important algorithms in data mining. Common classification algorithms such as decision tree, Bayesian network, support vector machine, association rules based classification algorithm and K-nearest neighbor algorithm have been widely used. This paper introduces the classical classification algorithm, compares the advantages and disadvantages of each algorithm and the latest research progress of each algorithm.
引用
收藏
页码:364 / 370
页数:7
相关论文
共 21 条
[1]  
Aljuboori A, 2016, NEW STRATEGY CASE BA
[2]   WCBA: Weighted classification based on association rules algorithm for breast cancer disease [J].
Alwidian, Jaber ;
Hammo, Bassam H. ;
Obeid, Nadim .
APPLIED SOFT COMPUTING, 2018, 62 :536-549
[3]  
Azad C., 2019, 2 INT C MICR COMP CO, P141
[4]  
Bing Liu, 1998, Proceedings Fourth International Conference on Knowledge Discovery and Data Mining, P80
[5]  
CHEN L, 2017, COMPUTER ENG APPL, V54, P161, DOI DOI 10.1007/S11204-017-9451-7
[6]   Very Fast C4.5 Decision Tree Algorithm [J].
Cherfi, Anis ;
Nouira, Kaouther ;
Ferchichi, Ahmed .
APPLIED ARTIFICIAL INTELLIGENCE, 2018, 32 (02) :119-137
[7]   Bayesian network classifiers [J].
Friedman, N ;
Geiger, D ;
Goldszmidt, M .
MACHINE LEARNING, 1997, 29 (2-3) :131-163
[8]   K-Nearest Neighbours Method as a Tool for Failure Rate Prediction [J].
Kutylowska, Malgorzata .
PERIODICA POLYTECHNICA-CIVIL ENGINEERING, 2018, 62 (02) :318-322
[9]   A novel software defect prediction based on atomic class-association rule mining [J].
Shao, Yuanxun ;
Liu, Bin ;
Wang, Shihai ;
Li, Guoqi .
EXPERT SYSTEMS WITH APPLICATIONS, 2018, 114 :237-254
[10]   MEASURING THE VC-DIMENSION OF A LEARNING-MACHINE [J].
VAPNIK, V ;
LEVIN, E ;
LECUN, Y .
NEURAL COMPUTATION, 1994, 6 (05) :851-876