A Model for Feature Selection with Binary Particle Swarm Optimisation and Synthetic Features

Recognising patterns and inferring nonlinearities between data that are seemingly random and stochastic in nature is one of the strong suites of machine learning models. Given a set of features, the ability to distinguish between useful features and seemingly useless features, and thereafter extract...

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Autores principales:	Samuel Olusegun Ojo, Juliana Adeola Adisa, Pius Adewale Owolawi, Chunling Tu
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-07-01
Colección:	AI
Materias:	feature selection synthetic features LSTM correlation Particle Swarm Optimisation stock market
Acceso en línea:	https://www.mdpi.com/2673-2688/5/3/60
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