Additional file 7 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_7_of_Harmonization_of_supervised_machine_learning_practices_for_efficient_source_attribution_of_Listeria_monocytogenes_based_on_genomic_data/24597610/1
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资源简介：
Additional file 7. Metrics of machine learning performance from different combinations of genomic profiles (i.e. 7‑locus alleles, core alleles, accessory genes, core SNPs and pan kmers), dataset splitting (i.e. 50, 60, 70, 80 and 90% of training dataset), data preprocessing (i.e. with or without near‑zero variance removal), and machine learning models.
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
