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. 2021 Dec 17;11:24138. doi: 10.1038/s41598-021-03019-y

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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FS analysis of CPIO-FS model. The results depicted that the CPIO-FS technique has chosen an optimal set of features from the applied dataset. For instance, on the test Epsilon dataset, the CIPO-FS technique selected a set of 1167 features out of 2000 features. In addition, on the applied ECBDL14-ROS technique, the CIPO-FS technique has chosen a collection of 631 features out of 386 features.