Assessment of predictive power of the classifiers Lasso/Logistic regression, Random Forests, and XGBoost for all ME/CFS patients, ME/CFS patients with sr-IBS, and ME/CFS patients without sr-IBS, when compared to the control group.

Milivojevic, Milica; Che, Xiaoyu; Bateman, Lucinda; Cheng, Aaron; Garcia, Benjamin A.; Hornig, Mady; Huber, Manuel; Klimas, Nancy G.; Lee, Bohyun; Lee, Hyoungjoo; Levine, Susan; Montoya, Jose G.; Peterson, Daniel L.; Komaroff, Anthony L.; Lipkin, W. Ian

doi:10.1371/journal.pone.0236148.s007

pone.0236148.s007.pdf (35.97 kB)

Assessment of predictive power of the classifiers Lasso/Logistic regression, Random Forests, and XGBoost for all ME/CFS patients, ME/CFS patients with sr-IBS, and ME/CFS patients without sr-IBS, when compared to the control group.

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posted on 21.07.2020, 17:31 authored by Milica Milivojevic, Xiaoyu Che, Lucinda Bateman, Aaron Cheng, Benjamin A. Garcia, Mady Hornig, Manuel Huber, Nancy G. Klimas, Bohyun Lee, Hyoungjoo Lee, Susan Levine, Jose G. Montoya, Daniel L. Peterson, Anthony L. Komaroff, W. Ian Lipkin

ME/CFS: myalgic encephalomyelitis/chronic fatigue syndrome, sr-IBS: self-reported irritable bowel syndrome, AUC: area under the curve, CI: confidence interval.

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Assessment of predictive power of the classifiers Lasso/Logistic regression, Random Forests, and XGBoost for all ME/CFS patients, ME/CFS patients with sr-IBS, and ME/CFS patients without sr-IBS, when compared to the control group.

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