Schizophrenia Classification Using Fuzzy Kernel C-Means

S. Hartini, Z. Rustam

Research output: Contribution to journalConference articlepeer-review

Abstract

Schizophrenia is a severe mental disorder that induces the mind, feeling, and behavior. Earlier treatment for this disease is essential; therefore, the ability to predict schizophrenia also becomes essential. Fuzzy kernel c-means was proposed in this research, utilizing the data obtained from Northwestern University, which consists of 171 schizophrenia and 221 non-schizophrenia samples. There are several kernel functions; however, RBF and polynomial kernel function were used. As the evaluation, k-fold cross-validation with k = 3, 5, 7, and 10 was used, and each of the performances was analyzed. From the experiments, it was concluded that fuzzy kernel c-means using RBF kernel with s = 0.01 and s = 1 provides better performance than polynomial kernel with a similar running time with fuzzy c-means.

Original languageEnglish
Article number012039
JournalJournal of Physics: Conference Series
Volume1752
Issue number1
DOIs
Publication statusPublished - 15 Feb 2021
Event3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019 - Makassar, Indonesia
Duration: 9 Oct 201910 Oct 2019

Keywords

  • fuzzy kernel C-means
  • Schizophrenia classification

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