Eigenvalue based spectral classification

PLoS One. 2023 Apr 6;18(4):e0283413. doi: 10.1371/journal.pone.0283413. eCollection 2023.

Abstract

This paper describes a new method of classification based on spectral analysis. The motivations behind developing the new model were the failures of the classical spectral cluster analysis based on combinatorial and normalized Laplacian for a set of real-world datasets of textual documents. Reasons of the failures are analysed. While the known methods are all based on usage of eigenvectors of graph Laplacians, a new classification method based on eigenvalues of graph Laplacians is proposed and studied.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Cluster Analysis

Grants and funding

This study was funded by Polish Ministry of Education and Science as well as by NCBiR (National Center for Research and Development) within the INSTATCENY project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.