A Novel Hybrid JFA-SVM Algorithm for Feature Selection-Reference-Cited by-同舟云学术

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A Novel Hybrid JFA-SVM Algorithm for Feature Selection

Published:2022 Issue: Volume: Page:439-447
ISSN:2190-3018
Container-title:Smart Intelligent Computing and Applications, Volume 2
language:
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Author:

Sahu Bibhuprasad,Sahoo Nibedita,Panigrahi Satya Sobhan,Rout Saroja Kumar

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-9705-0_43

Reference15 articles.

1. Aher, C.N., Jena, A.K.: Rider-chicken optimization dependent recurrent neural network for cancer detection and classification using gene expression data. Comput. Methods Biomechan. Biomed. Eng. Imag. Vis. 9(2), 174–191 (2021). able at SSRN 3545096 (2020)

2. Bidar, M., Kanan, H.R.: Jumper firefly algorithm. In: ICCKE 2013, IEEE, Mashhad, Iran (2010)

3. Panigrahi, S.S., Jena, A.K.: Optimization of test cases in object-oriented systems using fractional-SMO. Int. J. Open Source Softw. Proces. (IJOSSP) 12(1), 41–59 (2021)

4. Sahu, B., et al.: An intelligence-based health biomarker identification system using microarray analysis. Appl. Intel. Decis. Making Mach. Learn. 137–161 (2020)

5. Sahu, B., et al.: CDA-SVM: A chaotic dragonfly enriched support vector machine for micro array data sets. In: 2021 International Conference on Emerging Smart Computing and Informatics (ESCI), India (2021)

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1. Binary Optimization Using Hybrid Owl Optimization For Biomarker Selection From Cancer Datasets;2023 IEEE 3rd International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET);2023-02-10

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