AMCGWO : An enhanced feature selection based on swarm optimization for effective disease prediction

Missing data in datasets remain as a difficulty in terms of data analysis in various research fields, especially in the medical field, as it affects the treatment and diagnosis that the patient should receive. An enhanced imputation model using MFWCP (Mode Fuzzy Weight based Canonical Polyadic) and...

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Veröffentlicht in:	Journal of discrete mathematical sciences & cryptography Jg. 25; H. 3; S. 635 - 647
Hauptverfasser:	Lavanya, S. R., Mallika, R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Taylor & Francis 03.04.2022
Schlagworte:	68W50 Evolutionary algorithms Adaptive Mean Chaotic Grey Wolf Optimizer (AMCGWO) Bayesian network Breast cancer Feature selection genetic algorithms (computational aspects) Heart disease Missing value imputation Mode Fuzzy Weight based Canonical Polyadic (MFWCP)
ISSN:	0972-0529, 2169-0065
Online-Zugang:	Volltext
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