Genetic Clustering Algorithm-Based Feature Selection and Divergent Random Forest for Multiclass Cancer Classification Using Gene Expression Data

Genetic Clustering Algorithm-Based Feature Selection and Divergent Random Forest for Multiclass Cancer Classification Using Gene Expression Data

Abstract Computational identification and classification of clinical disorders gather major importance due to the effective improvement of machine learning methodologies. Cancer identification and classification are essential clinical areas to address, where accurate classification for multiple type...

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Bibliographic Details
Main Authors: L. Senbagamalar, S. Logeswari
Format: Article
Language:English
Published: Springer 2024-02-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Feature selection
Genetic cluster algorithm
Mutation
Divergent random forest
Multiclass classification
Online Access:https://doi.org/10.1007/s44196-024-00416-9

Internet

https://doi.org/10.1007/s44196-024-00416-9

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