Additional file 10 of Harmonization of supervised machine learning practices for efficient source attribution of Listeria monocytogenes based on genomic data
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https://springernature.figshare.com/articles/dataset/Additional_file_10_of_Harmonization_of_supervised_machine_learning_practices_for_efficient_source_attribution_of_Listeria_monocytogenes_based_on_genomic_data/24597619/1
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Additional file 10. Phenotype class‑dependent metrics estimated from the testing dataset with ML settings recommended in the present study (i.e. 80% of training dataset splitting, no near‑zero variance removal and SVM model) from 7‑locus alleles (A), core alleles (B), accessory genes (C), core SNPs (D) and pan kmers (E).
提供机构：
Di Pasquale, Adriano; Bucciacchio, Andrea; Castelli, Pierluigi; De Ruvo, Andrea; D’Alterio, Nicola; Cammà, Cesare; Radomski, Nicolas
创建时间：
2023-11-21
