Minimum Variance-Embedded Deep Kernel Regularized least squares Method for One-class Classification and Its Applications to Biomedical Data

HARI MOHAN PANDEY, Chandan Gautam, Pratik K Mishra, Aruna Tiwari, Bharat Richhariya, Shuihua Wang, M. Tanveer

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Deep kernel learning has been well explored for multi-class classification tasks; however, relatively less work is done for one-class classification (OCC). OCC needs samples from only one class to train the model. Most recently, kernel regularized least squares (KRL) method-based deep architecture is developed for the OCC task. This paper introduces a novel extension of this method by embedding minimum variance information within this architecture. This embedding improves the generalization capability of the classifier by reducing the intra-class variance. In contrast to traditional deep learning methods, this method can effectively work with small-size datasets. We conduct a comprehensive
set of experiments on 18 benchmark datasets (13 biomedical and 5 other datasets) to demonstrate the performance of the proposed classifier. We compare the results with 16 state-of-the-art one-class classifiers. Further, we also test our method for 2 real-world biomedical datasets viz.; detection of Alzheimer’s disease from structural magnetic resonance imaging data and detection of breast cancer from histopathological images. Proposed method exhibits more than 5% F1 score compared to existing state-of-the-art methods for various biomedical benchmark datasets. This makes it viable for application in biomedical fields where relatively less amount of data is available.
Original languageEnglish
Pages (from-to)191-216
JournalNeural Networks
Volume123
Early online date12 Dec 2019
DOIs
Publication statusE-pub ahead of print - 12 Dec 2019

Keywords

  • One-Class Classification
  • Kernel Learning
  • Outlier Detection
  • Alzheimer’s Disease
  • Magnetic Resonance Imaging
  • Breast cancer

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  • Research Output

    • 2 Citations
    • 1 Article

    A Dimension-Reduction Based Multilayer Perception Method for Supporting the Medical Decision Making

    Shin-Jye Lee, Ching-Hsun Tseng, G. T. –R. Lin, Yun Yang, Po Yang & Khan Muhammad, 27 Nov 2019, In : Pattern Recognition Letters.

    Research output: Contribution to journalArticle

  • 2 Citations (Scopus)

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