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). Yu Zhang Jennifer L. Pechal Carl J. Schmidt Heather R. Jordan Wesley W. Wang M. Eric Benbow Sing-Hoi Sze Aaron M. Tarone 10.1371/journal.pone.0213829.t002 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> 2019-04-15 17:27:09 PMI modeling postmortem microbiomes death investigation method 188 death cases findings Postmortem microbiomes population study Background