Fast C4.5

被引:0
|
作者
He, Ping [1 ]
Chen, Ling [1 ]
Xu, Xiao-Hua [2 ]
机构
[1] Yangzhou Univ, Dept Comp Sci, Yangzhou 225009, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Dept Comp Sci & Engn, Nanjing 210016, Peoples R China
关键词
classification; C4.5; fast; indirect bucket-sort; bit-parallel technique;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
C4.5 is a well-known machine learning algorithm used extensively, however, its runtime performance is sacrificed for the consideration of the limited main memory at that time. We present a fast implementation of C4.5 algorithm, named FC4.5(Fast C4.5). It organizes novel data structures, uses the indirect bucket-sort combined with the bit-parallel technique, and confines the binary-search of the cutoff within the narrowest range. The combination of these techniques enables FC4.5 greatly accelerates the tree construction process of C4.5 algorithm. Experiments show that FC4.5 can build the same decision tree as C4.5 (Release 8) system and the runtime performance gain up to 5.8 times. Besides, FC4.5 also achieves a good scalability on different kinds of datasets.
引用
收藏
页码:2841 / +
页数:2
相关论文
共 50 条
  • [1] Fast Numerical Threshold Search Algorithm for C4.5
    Chong, Wen-Mau
    Goh, Chien-Le
    Bau, Yoon-Teck
    Lee, Kian-Chin
    [J]. 2014 IIAI 3RD INTERNATIONAL CONFERENCE ON ADVANCED APPLIED INFORMATICS (IIAI-AAI 2014), 2014, : 930 - 935
  • [2] Very Fast C4.5 Decision Tree Algorithm
    Cherfi, Anis
    Nouira, Kaouther
    Ferchichi, Ahmed
    [J]. APPLIED ARTIFICIAL INTELLIGENCE, 2018, 32 (02) : 119 - 137
  • [3] A Comparative Analysis of Pruning Methods for C4.5 and Fuzzy C4.5
    Naseer, Tayyeba
    Asghar, Sohail
    Zhuang, Yan
    Fong, Simon
    [J]. ADVANCES IN DIGITAL TECHNOLOGIES, 2015, 275 : 304 - 312
  • [4] Efficient C4.5
    Ruggieri, S
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2002, 14 (02) : 438 - 444
  • [5] A fast and distributed C4.5 algorithm for urban big data
    Cheng, Wan-Shu
    Huang, Peng-Yu
    Huang, Jheng-Yu
    Chen, Ju-Chin
    Lin, Kawuu W.
    [J]. INTELLIGENT DATA ANALYSIS, 2023, 27 (05) : 1379 - 1408
  • [6] C4.5 decision forests
    Ho, TK
    [J]. FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2, 1998, : 545 - 549
  • [7] Bagging, boosting, and C4.5
    Quinlan, JR
    [J]. PROCEEDINGS OF THE THIRTEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE, VOLS 1 AND 2, 1996, : 725 - 730
  • [8] C4.5算法的优化
    黄秀霞
    孙力
    [J]. 计算机工程与设计, 2016, 37 (05) : 1265 - 1270
  • [9] The Application and Research of C4.5 Algorithm
    Zhao, Hongyan
    [J]. APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY, 2014, 513-517 : 1285 - 1288
  • [10] Credal C4.5 with Refinement of Parameters
    Mantas, Carlos J.
    Abellan, Joaquin
    Castellano, Javier G.
    Cano, Jose R.
    Moral, Serafin
    [J]. INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: APPLICATIONS, IPMU 2018, PT III, 2018, 855 : 739 - 747