FEATURE CLUSTERING FOR PSO-BASED FEATURE CONSTRUCTION ON HIGH-DIMENSIONAL DATA

FEATURE CLUSTERING FOR PSO-BASED FEATURE CONSTRUCTION ON HIGH-DIMENSIONAL DATA

Feature construction (FC) refers to a process that uses the original features to construct new features with better discrimination ability. Particle Swarm Optimisation (PSO) is an effective search technique that has been successfully utilised in FC. However, the application of PSO for feature const...

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Bibliografiska uppgifter
Huvudupphovsmän: Idheba Mohamad Ali Omer Swesi, Azuraliza Abu Bakar
Materialtyp: Artikel
Språk:English
Publicerad: UUM Press 2019-09-01
Serie:Journal of ICT
Ämnen:
Particle swarm optimisation
feature construction
genetic programming
classification
high-dimensional data
Länkar:https://e-journal.uum.edu.my/index.php/jict/article/view/12327

Internet

https://e-journal.uum.edu.my/index.php/jict/article/view/12327

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