Orthogonal Non-Negative Matrix Factorization using Ridge Term for Classifying Expressed Gene

Diyah Utami Kusumaning Putri, Aina Musdholifah, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This research provides the development of Non-Negative Matrix Factorization method for classifying gene expression data. Furthermore, we also compare the NMF method with Uni-Orthogonal NMF for classifying the data. We use two schemas of datasets which use complete dataset and incomplete dataset. The incomplete dataset contains missing values which used to prove that the methods can handle the missing values problem on the classification problem. Sparse regularization in dimensionality reduction using ridge term (Lz-Norm) is applied in this study to see the effect of sparse regularization in the incomplete dataset. In this paper, we propose an approach to classify the diseases from gene expression data using the combination of matrix factorization methods and support vector machine (SVM). The experimental results show that adding ridge term in Y-orthogonal NMF make accuracy higher in training data with incomplete data. Y-orthogonal NMF using ridge term is the best method for classifying expressed genes with incomplete data than the other compared methods.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Advanced Informatics
Subtitle of host publicationConcepts, Theory, and Applications, ICAICTA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728134505
DOIs
StatePublished - Sep 2019
Event2019 International Conference on Advanced Informatics: Concepts, Theory, and Applications, ICAICTA 2019 - Yogyakarta, Indonesia
Duration: 20 Sep 201922 Sep 2019

Publication series

NameProceedings - 2019 International Conference on Advanced Informatics: Concepts, Theory, and Applications, ICAICTA 2019

Conference

Conference2019 International Conference on Advanced Informatics: Concepts, Theory, and Applications, ICAICTA 2019
Country/TerritoryIndonesia
CityYogyakarta
Period20/09/1922/09/19

Keywords

  • feature extraction
  • gene expression data
  • nonnegative matrix factorization
  • orthogonal constraint
  • ridge term

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