Ensemble learning: A survey

被引：1881
作者：
Sagi, Omer [1 ]
Rokach, Lior [1 ]
机构：
[1] Ben Gurion Univ Negev, Dept Software & Informat Syst Engn, Beer Sheva, Israel
来源：
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY | 2018年 / 8卷 / 04期
基金：
加拿大自然科学与工程研究理事会; 美国国家科学基金会;
关键词：
boosting; classifier combination; ensemble models; machine-learning; mixtures of experts; multiple classifier system; random forest; CLASSIFIER ENSEMBLES; ROTATION FOREST; NEURAL-NETWORKS; CONSENSUS; ALGORITHMS; MODEL; TREES;
D O I：
10.1002/widm.1249
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ensemble methods are considered the state-of-the art solution for many machine learning challenges. Such methods improve the predictive performance of a single model by training multiple models and combining their predictions. This paper introduce the concept of ensemble learning, reviews traditional, novel and state-of-the-art ensemble methods and discusses current challenges and trends in the field. This article is categorized under: Algorithmic Development > Model Combining Technologies > Machine Learning Technologies > Classification
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页数：18
相关论文
共 153 条
  • [71] Jiang X., 2017, COMPUTATIONAL INTELL, V2017, P1
  • [72] Kamath C., 2001, REATING ENSEMBLES DE
  • [73] Multilevel hypergraph partitioning: Applications in VLSI domain
    Karypis, G
    Aggarwal, R
    Kumar, V
    Shekhar, S
    [J]. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 1999, 7 (01) : 69 - 79
  • [74] Kiselev VY, 2017, NAT METHODS, V14, P483, DOI [10.1038/NMETH.4236, 10.1038/nmeth.4236]
  • [75] Kolter JZ, 2003, THIRD IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS, P123
  • [76] Deep Neural Decision Forests
    Kontschieder, Peter
    Fiterau, Madalina
    Criminisi, Antonio
    Bulo, Samuel Rota
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2015, : 1467 - 1475
  • [77] Kulkarni V.Y., 2013, Int J Adv Comput, V36, P1144
  • [78] Multi-view ensemble learning: an optimal feature set partitioning for high-dimensional data classification
    Kumar, Vipin
    Minz, Sonajharia
    [J]. KNOWLEDGE AND INFORMATION SYSTEMS, 2016, 49 (01) : 1 - 59
  • [79] Kuncheva L., 2004, COMBINING PATTERN CL, DOI 10.1002/0471660264
  • [80] Parameter determination and feature selection for C4.5 algorithm using scatter search approach
    Lin, Shih-Wei
    Chen, Shih-Chieh
    [J]. SOFT COMPUTING, 2012, 16 (01) : 63 - 75
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