S2 Table -

Performance of MCount using globally optimized hyperparameters ( and ) across 10 sub-datasets. The table presents the average error rates for each sub-dataset when applying the global optimal hyperparameters. The results indicate that MCount maintains robust performance across varied experimental conditions, with error rates significantly lower than those achieved by NICE. (DOCX)

Publication Details

Journal
Figshare
Published
2025-03-19
DOI
https://doi.org/10.1371/journal.pone.0311242.s006
Primary Topic
Machine Learning and Data Classification
Type
article
Field-Weighted Citation Impact
0.00
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S2 Table -

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Machine Learning and Data Classification
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S2 Table -

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Abstract

Performance of MCount using globally optimized hyperparameters ( and ) across 10 sub-datasets. The table presents the average error rates for each sub-dataset when applying the global optimal hyperparameters. The results indicate that MCount maintains robust performance across varied experimental conditions, with error rates significantly lower than those achieved by NICE. (DOCX)

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Openalex Percentile: Top 76%
Machine Learning and Data Classification
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