#machine learning
Apr 2026
Assessing the impact of dimensionality reduction on clustering performance - a systematic study
The influence of five dimensionality reduction techniques - Principal Component Analysis (PCA), Kernel Principal Component Analysis (Kernel PCA), Variational Autoencoder (VAE), Isometric Mapping (Isomap), and Multidimensional Scaling (MDS) - on the performance of four popular clustering algorithms is assessed.
Ousmane Assani Amate, Elyes Lounissi, Mohammadreza Bakhtyari et al.
· arXiv.org · 1 citation