IDEPI performance in predicting phenotype and recovering features from simulated data.
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https://figshare.com/articles/dataset/_IDEPI_performance_in_predicting_phenotype_and_recovering_features_from_simulated_data_/1182868
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Forward feature selection (to optimize MCC), and 10-fold nested cross-validation were used to learn the models. L: the number of sites in an epitope; M: how many escape mutations are needed to confer resistance; epitope recover classes are based on simulated evolutionary rates; FP: mean (per replicate) number of selected features not in a simulated epitope; a feature was counted as recovered if it were selected in 50% or more of cross-validation replicates.
IDEPI performance in predicting phenotype and recovering features from simulated data.
创建时间：
2014-09-25
