Projection Pursuit

Projection pursuit is a dimensionality reduction technique aiming to identify interesting low-dimensional projections of high-dimensional data by maximizing a chosen index function, revealing underlying structure and facilitating visualization. Current research focuses on optimizing projection pursuit indices using various algorithms, including swarm-based optimizers like the Jellyfish Search Optimizer, and integrating it with other techniques such as Naive Bayes classification and optimal transport for generative modeling. These advancements improve the efficiency and effectiveness of projection pursuit in diverse applications, ranging from multi-robot exploration and target interception to analyzing complex datasets in fields like molecular dynamics and machine learning.