Correction to: Adaptive random forests for evolving data stream classification

被引:0
|
作者
Heitor M. Gomes
Albert Bifet
Jesse Read
Jean Paul Barddal
Fabrício Enembreck
Bernhard Pfahringer
Geoff Holmes
Talel Abdessalem
机构
[1] Pontifícia Universidade Católica do Paraná,PPGIa
[2] Université Paris-Saclay,LTCI, Télécom ParisTech
[3] École Polytechnique,LIX
[4] University of Waikato,Department of Computer Science
[5] National University of Singapore,UMI CNRS IPAL & School of Computing
来源
Machine Learning | 2019年 / 108卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
The Publisher regrets an error in the spelling of the family name of the sixth author. The correct spelling is Bernhard Pfahringer, as it appears in the author list above.
引用
收藏
页码:1877 / 1878
页数:1
相关论文
共 50 条
  • [31] On Robustness of Adaptive Random Forest Classifier on Biomedical Data Stream
    Fatlawi, Hayder K.
    Kiss, Attila
    INTELLIGENT INFORMATION AND DATABASE SYSTEMS (ACIIDS 2020), PT I, 2020, 12033 : 332 - 344
  • [32] Oxides Classification with Random Forests
    Xiao, Kai
    Chen, Baitong
    Bao, Wenzheng
    Cheng, Honglin
    INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2022, PT II, 2022, 13394 : 680 - 686
  • [33] SPATIALLY ADAPTIVE RANDOM FORESTS
    Geremia, Ezequiel
    Menze, Bjoern H.
    Ayache, Nicholas
    2013 IEEE 10TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 2013, : 1344 - 1347
  • [34] Random forests for classification in ecology
    Cutler, D. Richard
    Edwards, Thomas C., Jr.
    Beard, Karen H.
    Cutler, Adele
    Hess, Kyle T.
    ECOLOGY, 2007, 88 (11) : 2783 - 2792
  • [35] Classification and interaction in random forests
    Denisko, Danielle
    Hoffman, Michael M.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2018, 115 (08) : 1690 - 1692
  • [36] Evolving granular neural network for semi-supervised data stream classification
    Leite, Daniel
    Costa, Pyramo, Jr.
    Gomide, Fernando
    2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010, 2010,
  • [37] Grid-based high performance ensemble classification for evolving data stream
    Qian, Quan
    Xie, Mengbo
    Xiao, Chaojie
    Zhang, Rui
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2016, 28 (16): : 4339 - 4351
  • [38] Multi-label classification via incremental clustering on an evolving data stream
    Tien Thanh Nguyen
    Manh Truong Dang
    Anh Vu Luong
    Liew, Alan Wee-Chung
    Liang, Tiancai
    McCall, John
    PATTERN RECOGNITION, 2019, 95 : 96 - 113
  • [39] Random forests and nearest shrunken centroids for the classification of sensor array data
    Pardo, Matteo
    Sberveglieri, Giorgio
    SENSORS AND ACTUATORS B-CHEMICAL, 2008, 131 (01) : 93 - 99
  • [40] AUTOMATIC FUSION AND CLASSIFICATION OF HYPERSPECTRAL AND LIDAR DATA USING RANDOM FORESTS
    Merentitis, Andreas
    Debes, Christian
    Heremans, Roel
    Frangiadakis, Nikolaos
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, : 1245 - 1248