Optimizing Leukemia Classification Through Nature-Inspired Feature Reduction and Stacked Ensemble Learning Algorithms-Reference-Cited by-同舟云学术

Optimizing Leukemia Classification Through Nature-Inspired Feature Reduction and Stacked Ensemble Learning Algorithms

Published:2024-05-02 Issue: Volume:30 Page:1-6
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Container-title:2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC)
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Author:

Mohapatra Saumendra Kumar¹^ORCID,P Sharmila K.²,Mohanty Mihir Narayan³^ORCID

Affiliation:

1. Sri Sri University,Faculty of Engineering & Technology,Cuttack,Odisha,India

2. CMR Institute of Technology,Department of ECE,Bangalore,India

3. ITER, Siksha ‘O’ Anusandhan (Deemed to be University),Department of Electronics & Communication Engineering,Bhubaneswar,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592863/10592866/10593969.pdf?arnumber=10593969

Reference14 articles.

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2. Enhancing chronic lymphocytic leukemia classification through nature-inspired feature reduction and stacked ensemble learning algorithms;Smith;Bioinformatics Research and Applications,2019

3. Hybrid feature selection approach using GA and PSO for ALL subtype classification;Khan;International Journal of Scientific Research in Computer Science, Engineering and Information Technology,2018

4. Grey wolf optimizer-based feature selection for AML subtype classification;Li;International Journal of Computers Communications & Control,2020

5. Stacked ensemble model for leukemia subtype classification using deep learning;He;IEEE/ ACM Transactions on Computational Biology and Bioinformatics,2019