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Modern Approaches for Intelligent Information and Database Systems pp 233–243Cite as

A Coupling Support Vector Machines with the Feature Learning of Deep Convolutional Neural Networks for Classifying Microarray Gene Expression Data

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 769))

Abstract

Support vector machines (SVM) and deep convolutional neural networks (DCNNs) are state-of-the-art classification techniques in many real-world applications. Our investigation aims at proposing a hybrid model combining DCNNs and SVM (called DCNN-SVM) to effectively predict very-high-dimensional gene expression data. The DCNN-SVM trains the DCNNs model to automatically extract features from microarray gene expression data and followed which the DCNN-SVM learns a non-linear SVM model to classify gene expression data. Numerical test results on 15 microarray datasets from Array Expression and Medical Database (Kent Ridge) show that our proposed DCNN-SVM is more accurate than the classical DCNNs algorithm, SVM, random forests.

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Author information

Authors and Affiliations

  1. An Giang University, An Giang, Vietnam

    Phuoc-Hai Huynh & Van-Hoa Nguyen

  2. Can Tho University, Can Tho, Vietnam

    Thanh-Nghi Do

Authors
  1. Phuoc-Hai Huynh
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  2. Van-Hoa Nguyen
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  3. Thanh-Nghi Do
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Corresponding authors

Correspondence to Phuoc-Hai Huynh , Van-Hoa Nguyen or Thanh-Nghi Do .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Wrocław University of Science and Technology, Wrocław, Poland

    Andrzej Sieminski

  2. Department of Information Systems, Wrocław University of Science and Technology, Wrocław, Poland

    Adrianna Kozierkiewicz

  3. Department of Information Systems and Computing, Complutense University of Madrid, Madrid, Spain

    Manuel Nunez

  4. Faculty of Information Technology, Vietnam National University, Hanoi, Vietnam

    Quang Thuy Ha

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Huynh, PH., Nguyen, VH., Do, TN. (2018). A Coupling Support Vector Machines with the Feature Learning of Deep Convolutional Neural Networks for Classifying Microarray Gene Expression Data. In: Sieminski, A., Kozierkiewicz, A., Nunez, M., Ha, Q. (eds) Modern Approaches for Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-319-76081-0_20

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  • DOI: https://doi.org/10.1007/978-3-319-76081-0_20

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  • Online ISBN: 978-3-319-76081-0

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