A noise-resilient online learning algorithm with ramp loss for ordinal regression

被引:0
|
作者
Zhang, Maojun [1 ,2 ]
Zhang, Cuiqing [2 ]
Liang, Xijun [3 ]
Xia, Zhonghang [4 ]
Jian, Ling [5 ]
Nan, Jiangxia [1 ]
机构
[1] Suzhou Univ Sci & Technol, Sch Business, Suzhou, Jiangsu, Peoples R China
[2] Guilin Univ Elect Technol, Sch Math & Comp Sci, Guilin 541004, Guangxi, Peoples R China
[3] China Univ Petr, Coll Sci, Qingdao, Shandong, Peoples R China
[4] Western Kentucky Univ, Sch Engn & Appl Sci, Bowling Green, KY 42101 USA
[5] China Univ Petr, Sch Econ & Management, Qingdao, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Ordinal regression; online learning; PA-RAMP algorithm; ramp loss; SUPPORT VECTOR MACHINE; MARGIN; MODELS; ROBUST;
D O I
10.3233/IDA-205613
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Ordinal regression has been widely used in applications, such as credit portfolio management, recommendation systems, and ecology, where the core task is to predict the labels on ordinal scales. Due to its learning efficiency, online ordinal regression using passive aggressive (PA) algorithms has gained a much attention for solving large-scale ranking problems. However, the PA method is sensitive to noise especially in the scenario of streaming data, where the ranking of data samples may change dramatically. In this paper, we propose a noise-resilient online learning algorithm using the Ramp loss function, called PA-RAMP, to improve the performance of PA method for noisy data streams. Also, we validate the order preservation of thresholds of the proposed algorithm. Experiments on real-world data sets demonstrate that the proposed noise-resilient online ordinal regression algorithm is more robust and efficient than state-of-the-art online ordinal regression algorithms.
引用
收藏
页码:379 / 405
页数:27
相关论文
共 49 条
  • [1] A Noise-Resilient Online Learning Algorithm for Scene Classification
    Jian, Ling
    Gao, Fuhao
    Ren, Peng
    Song, Yunquan
    Luo, Shihua
    [J]. REMOTE SENSING, 2018, 10 (11)
  • [2] Fuzzy-Based, Noise-Resilient, Explainable Algorithm for Regression
    Viana, Javier
    Cohen, Kelly
    [J]. EXPLAINABLE AI AND OTHER APPLICATIONS OF FUZZY TECHNIQUES, NAFIPS 2021, 2022, 258 : 461 - 472
  • [3] Canal-LASSO: A sparse noise-resilient online linear regression model
    Lei, Hejie
    Chen, Xingke
    Jian, Ling
    [J]. INTELLIGENT DATA ANALYSIS, 2020, 24 (05) : 993 - 1010
  • [4] A noise-resilient equalization algorithm for OFDM systems
    Ge, QH
    Lu, JH
    Mei, SL
    [J]. 5TH INTERNATIONAL SYMPOSIUM ON WIRELESS PERSONAL MULTIMEDIA COMMUNICATIONS, VOLS 1-3, PROCEEDINGS, 2002, : 1314 - 1317
  • [5] Perceptron Ranking Using Interval Labels with Ramp Loss for Online Ordinal Regression
    Zhang, Cuiqing
    Zhang, Maojun
    Liang, Xijun
    Xia, Zhonghang
    Nan, Jiangxia
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020 (2020)
  • [6] Machine Learning of Noise-Resilient Quantum Circuits
    Cincio, Lukasz
    Rudinger, Kenneth
    Sarovar, Mohan
    Coles, Patrick J.
    [J]. PRX QUANTUM, 2021, 2 (01):
  • [7] Noise-resilient deep learning for integrated circuit tomography
    Guo, Zhen
    Liu, Zhiguang
    Barbastathis, George
    Zhang, Qihang
    Glinsky, Michael E.
    Alpert, Bradley K.
    Levine, Zachary H.
    [J]. OPTICS EXPRESS, 2023, 31 (10) : 15355 - 15371
  • [8] Noise-Resilient Ensemble Learning Using Evidence Accumulation
    Candel, Gaelle
    Naccache, David
    [J]. ADVANCED NETWORK TECHNOLOGIES AND INTELLIGENT COMPUTING, ANTIC 2021, 2022, 1534 : 374 - 388
  • [9] A Noise-Resilient Sparse Subspace Clustering Algorithm for Image Sequences
    Chen, Liping
    Guo, Gongde
    Wang, Hui
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2017, : 120 - 125
  • [10] Noise-Resilient Edge Detection Algorithm for Brain MRI Images
    Agaian, Sos
    Almuntashri, Ali
    [J]. 2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 3689 - 3692