Classification of cancer microarray data using a two-step feature selection framework with moth-flame optimization and extreme learning machine

Author:

Sucharita SwatiORCID,Sahu Barnali,Swarnkar Tripti,Meher Saroj K.

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference38 articles.

1. Ab Hamid TMT, Sallehuddin R, Yunos ZM, Ali A (2021) Ensemble based filter feature selection with harmonize particle swarm optimization and support vector machine for optimal cancer classification. Mach Learn Appl 5:100054

2. Abdulla M, Khasawneh MT (2020) G-Forest: an ensemble method for cost-sensitive feature selection in gene expression microarrays. Artif Intell Med 108:101941

3. Alomari OA, Makhadmeh SN, Al-Betar MA, Alyasseri ZAA, Doush IA, Abasi AK, … Zitar RA (2021) Gene selection for microarray data classification based on gray wolf optimizer enhanced with TRIZ-inspired operators. Knowl-Based Syst 223:107034

4. Alzaqebah M, Alrefai N, Ahmed EA, Jawarneh S, Alsmadi MK (2020) Neighborhood search methods with moth optimization algorithm as a wrapper method for feature selection problems. Int J Electr Comput Eng 10(4):3672

5. Arowolo MO, Abdulsalam SO, Saheed YK, Salawu MD (2016) A feature selection based on One-Way-Anova for microarray data classification. AJPAS J 3:1–6

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