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