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Neuroevolution-based multiobjective algorithm for feature selection and binary classification of DNA microarrays
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DOI：10.1016/j.asoc.2025.113520.png)
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Abstract
En 中文
• SMS-MONEAT optimises artificial neural networks’ topology and weights while performing feature selection simultaneously. • SMS-MONEAT showed promising performance in a two-objective optimisation task, aiming to minimise the number of features selected while also minimising the error of the generated models for microarray binary classification. • An external archive was included in SMS-MONEAT, which split the population depending on the subset of features selected to increase the population’s diversity.
Keywords:
Neuroevolution
Multiobjective optimisation
Feature selection
DNA microarray
Journal
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6.6
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Citations:
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