10.1371/journal.pone.0213829.t002 Yu Zhang Yu Zhang Jennifer L. Pechal Jennifer L. Pechal Carl J. Schmidt Carl J. Schmidt Heather R. Jordan Heather R. Jordan Wesley W. Wang Wesley W. Wang M. Eric Benbow M. Eric Benbow Sing-Hoi Sze Sing-Hoi Sze Aaron M. Tarone Aaron M. Tarone Accuracy and p-value obtained from 5-fold cross validation for three machine learning methods (xgboost, random forest and neural network) for the prediction of postmortem interval, event location and manner of death using the microbiota from all anatomic locations (ears, eyes, nose, mouth, and rectum). Public Library of Science 2019 PMI modeling postmortem microbiomes death investigation method 188 death cases findings Postmortem microbiomes population study Background 2019-04-15 17:27:09 Dataset https://plos.figshare.com/articles/dataset/Accuracy_and_p-value_obtained_from_5-fold_cross_validation_for_three_machine_learning_methods_xgboost_random_forest_and_neural_network_for_the_prediction_of_postmortem_interval_event_location_and_manner_of_death_using_the_microbiota_from_all_anatomic_loca/7994729 <p>Accuracy and p-value obtained from 5-fold cross validation for three machine learning methods (xgboost, random forest and neural network) for the prediction of postmortem interval, event location and manner of death using the microbiota from all anatomic locations (ears, eyes, nose, mouth, and rectum).</p>