New Metrics for Assessing Projection Pursuit Indexes, and Guiding Optimisation Choices

• URL: http://arxiv.org/abs/2407.13663v2
• Date: Mon, 14 Oct 2024 02:22:51 GMT
• Title: New Metrics for Assessing Projection Pursuit Indexes, and Guiding Optimisation Choices
• Authors: H. Sherry Zhang, Dianne Cook, Nicolas Langrené, Jessica Wai Yin Leung,
• Abstract summary: The projection pursuit (PP) guided tour interactively optimises a criterion function known as the PP index, to explore high-dimensional data by revealing interesting projections. optimisation of some PP indexes can be non-trivial, if they are non-smooth functions, or the optimum has a small "squint angle", detectable only from close proximity. This study investigates the performance of a recently introduced swarm-based algorithm, Jellyfish Search Optimiser (JSO), for optimising PP indexes.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The projection pursuit (PP) guided tour interactively optimises a criterion function known as the PP index, to explore high-dimensional data by revealing interesting projections. Optimisation of some PP indexes can be non-trivial, if they are non-smooth functions, or the optimum has a small "squint angle", detectable only from close proximity. To address these challenges, this study investigates the performance of a recently introduced swarm-based algorithm, Jellyfish Search Optimiser (JSO), for optimising PP indexes. The performance of JSO for visualising data is evaluated across various hyper-parameter settings and compared with existing optimisers. Additionally, methods for calculating the smoothness and squintability properties of the PP index are proposed. They are used to assess the optimiser performance in the presence of PP index complexities. A simulation study illustrates the use of these performance metrics to compare the JSO with existing optimisation methods available for the guided tour. The JSO algorithm has been implemented in the R package, `tourr`, and functions to calculate smoothness and squintability are available in the `ferrn` package.

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