Comparison between stochastic support vector machine (stochastic SVM) and Fuzzy Kernel Robust C-Means (FKRCM) in breast cancer classification

Z. Rustam, R. A. Putri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cancer is one of the most famous diseases in recent years. Cancer has various classifications, which are difficult to detect in patients. Most patients are diagnosed with cancer after being at an advanced stage. To analyze the disease and diagnose cancer in patient, we need gene expression data. Gene expression data contain so many genes, even thousands of genes, but not all of those genes contain information necessary to detect cancer for its classification. Machine learning can choose the important genes for the classification to reduce running time, cost, and increase classification accuracy. In this paper we use Stochastic SVM and Fuzzy Kernel Robust C-Means (FRKCM). Then we will compare the accuracy of the methods in breast cancer classification. Stochastic SVM achieves a high prediction accuracy by learning the optimal hyperplane from the training set, which greatly simplifies the classification and regression problems. Fuzzy Kernel Robust C-Means (FKRCM) will define the membership function, set specific data called prototype and use the learning rate on each iteration. Based on the experiment, we get 90.43 % accuracy for the Stochastic SVM and 95.65 % accuracy for Fuzzy Kernel Robust C-Means.

Original languageEnglish
Title of host publicationProceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018
EditorsTerry Mart, Djoko Triyono, Ivandini T. Anggraningrum
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419155
DOIs
Publication statusPublished - 4 Nov 2019
Event4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018 - Depok, Indonesia
Duration: 30 Oct 201831 Oct 2018

Publication series

NameAIP Conference Proceedings
Volume2168
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018
CountryIndonesia
CityDepok
Period30/10/1831/10/18

Keywords

  • Fuzzy C-means
  • fuzzy kernel robust C-means
  • kernel function
  • support vector machine (SVM)

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    Rustam, Z., & Putri, R. A. (2019). Comparison between stochastic support vector machine (stochastic SVM) and Fuzzy Kernel Robust C-Means (FKRCM) in breast cancer classification. In T. Mart, D. Triyono, & I. T. Anggraningrum (Eds.), Proceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018 [020048] (AIP Conference Proceedings; Vol. 2168). American Institute of Physics Inc.. https://doi.org/10.1063/1.5132475