Optimization-driven graph visualization of data clustering and classification dynamics

doi:10.1016/j.neucom.2026.133918

Optimization-driven graph visualization of data clustering and classification dynamics

2026-05-14

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Idriss Dagal

DOI：10.1016/j.neucom.2026.133918

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Abstract

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• Integrates evolutionary optimization with graph visualization for clustering. • Enhances cluster separability by up to over PCA and t-SNE. • Provides clearer representation of nonlinear classification boundaries. • Reveals algorithm-specific convergence and misclassification patterns. • Offers a diagnostic tool for robust, transparent model evaluation.

Keywords:

clustering

graph visualization

evolutionary optimization

nonlinear classification

model evaluation

Optimization-driven graph visualization of data clustering and classification dynamics

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