Learning Optimal Decision Trees Under Memory Constraints

被引:2
|
作者
Aglin, Gael [1 ]
Nijssen, Siegfried [1 ]
Schaus, Pierre [1 ]
机构
[1] UCLouvain, ICTEAM, Louvain La Neuve, Belgium
关键词
Decision trees; Optimization; Memory management;
D O I
10.1007/978-3-031-26419-1_24
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Existing algorithms for learning optimal decision trees can be put into two categories: algorithms based on the use of Mixed Integer Programming (MIP) solvers and algorithms based on dynamic programming (DP) on itemsets. While the algorithms based on DP are the fastest, their main disadvantage compared to MIP-based approaches is that the amount of memory these algorithms may require to find an optimal solution is not bounded. Consequently, for some datasets these algorithms can only be executed on machines with large amounts of memory. In this paper, we propose the first DP-based algorithm for learning optimal decision trees that operates under memory constraints. Core contributions of this work include: (1) strategies for freeing memory when too much memory is used by the algorithm; (2) an effective approach for recovering the optimal decision tree when parts of the memory are freed. Our experiments demonstrate a favorable trade-off between memory constraints and the run times of our algorithm.
引用
下载
收藏
页码:393 / 409
页数:17
相关论文
共 50 条
  • [41] On Algorithm for Building of Optimal α-Decision Trees
    Alkhalid, Abdulaziz
    Chikalov, Igor
    Moshkov, Mikhail
    ROUGH SETS AND CURRENT TRENDS IN COMPUTING, PROCEEDINGS, 2010, 6086 : 438 - 445
  • [42] Approximating Optimal Binary Decision Trees
    Adler, Micah
    Heeringa, Brent
    ALGORITHMICA, 2012, 62 (3-4) : 1112 - 1121
  • [43] Learning fuzzy decision trees
    Apolloni, B
    Zamponi, G
    Zanaboni, AM
    NEURAL NETWORKS, 1998, 11 (05) : 885 - 895
  • [44] Transfer learning in decision trees
    Lee, Jun Won
    Giraud-Carrier, Christophe
    2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 726 - 731
  • [45] Agnostically Learning Decision Trees
    Gopalan, Parikshit
    Kalai, Adam Tauman
    Klivans, Adam R.
    STOC'08: PROCEEDINGS OF THE 2008 ACM INTERNATIONAL SYMPOSIUM ON THEORY OF COMPUTING, 2008, : 527 - +
  • [46] Competitive learning in decision trees
    Martinez, D
    COMPUTING ANTICIPATORY SYSTEMS: CASYS - FIRST INTERNATIONAL CONFERENCE, 1998, 437 : 660 - 670
  • [47] Decision Trees Learning System
    Paliwoda, M
    INTELLIGENT INFORMATION SYSTEMS 2002, PROCEEDINGS, 2002, 17 : 77 - 90
  • [48] Learning DNF by decision trees
    1600, Morgan Kaufmann Publ Inc, San Mateo, CA, USA (01):
  • [49] Anytime learning of decision trees
    Esmeir, Saher
    Markovitch, Shaul
    JOURNAL OF MACHINE LEARNING RESEARCH, 2007, 8 : 891 - 933
  • [50] Optimal routing table design for IP address lookups under memory constraints
    Univ of California, Berkeley, Berkeley, United States
    Proc IEEE INFOCOM, (1437-1444):