Fuzzy Linear Discriminant Analysis Clustering With Its Application

Authors

  • Iden Alkanani Department of mathematics, College of Science for Women , University of Baghdad, Baghdad, Iraq.
  • Rand Fawzi Department of mathematics , College of Education for Pure Science , Ibn-Al-Haitham, University of Baghdad, Baghdad, Iraq. https://orcid.org/0000-0003-0106-6688

Keywords:

clustering , fuzzy compactness and separation (FCS), fuzzy linear discriminant analysis (FLDA), validation clustering method

Abstract

Many fuzzy clustering are based on within-cluster scatter with a compactness measure , but in this paper explaining new fuzzy clustering method which depend on within-cluster scatter with a compactness measure and between-cluster scatter with a separation measure called the fuzzy compactness and separation (FCS). The fuzzy linear discriminant analysis (FLDA) based on within-cluster scatter matrix and between-cluster scatter matrix . Then two fuzzy scattering matrices in the objective function assure the compactness between data elements and cluster centers .To test the optimal number of clusters using validation clustering method is discuss .After that an illustrate example are applied.

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Published

2024-02-13

Issue

Section

Mathematics

How to Cite

Fuzzy Linear Discriminant Analysis Clustering With Its Application. (2024). Iraqi Journal of Science, 54(Mathematics conf), 739-743. https://ijs.uobaghdad.edu.iq/index.php/eijs/article/view/12449

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