| Quantifying uncertainty in random forests via confidence intervals and hypothesis tests L Mentch, G Hooker The Journal of Machine Learning Research 17 (1), 841-881, 2016 | 395 | 2016 |
| Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance G Hooker, L Mentch, S Zhou Statistics and Computing 31, 1-16, 2021 | 204 | 2021 |
| Please stop permuting features: An explanation and alternatives G Hooker, L Mentch arXiv preprint arXiv:1905.03151 2, 1, 2019 | 153 | 2019 |
| Randomization as regularization: A degrees of freedom explanation for random forest success L Mentch, S Zhou Journal of Machine Learning Research 21 (171), 1-36, 2020 | 87 | 2020 |
| Earlier Isn't Always Better: Sub-aspect Analysis on Corpus and System Biases in Summarization T Jung, D Kang, L Mentch, E Hovy arXiv preprint arXiv:1908.11723, 2019 | 55 | 2019 |
| Integrative modelling of tumour DNA methylation quantifies the contribution of metabolism M Mehrmohamadi, LK Mentch, AG Clark, JW Locasale Nature communications 7 (1), 13666, 2016 | 51 | 2016 |
| The importance of calibration in clinical psychology O Lindhiem, IT Petersen, LK Mentch, EA Youngstrom Assessment 27 (4), 840-854, 2020 | 49 | 2020 |
| R-CMap—An open-source software for concept mapping H Bar, L Mentch Evaluation and Program Planning 60, 284-292, 2017 | 49 | 2017 |
| Rates of convergence for random forests via generalized U-statistics W Peng, T Coleman, L Mentch Electronic Journal of Statistics 16 (1), 232-292, 2022 | 44 | 2022 |
| Formal hypothesis tests for additive structure in random forests L Mentch, G Hooker Journal of Computational and Graphical Statistics 26 (3), 589-597, 2017 | 44* | 2017 |
| Scalable and efficient hypothesis testing with random forests T Coleman, W Peng, L Mentch Journal of Machine Learning Research 23 (170), 1-35, 2022 | 34 | 2022 |
| Predictive inference with random forests: A new perspective on classical analyses RJ McAlexander, L Mentch Research & Politics 7 (1), 2053168020905487, 2020 | 34 | 2020 |
| Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction ML Wallace, L Mentch, BJ Wheeler, AL Tapia, M Richards, S Zhou, L Yi, ... BMC medical research methodology 23 (1), 144, 2023 | 29 | 2023 |
| Trees, forests, chickens, and eggs: when and why to prune trees in a random forest S Zhou, L Mentch Statistical Analysis and Data Mining: The ASA Data Science Journal 16 (1), 45-64, 2023 | 25 | 2023 |
| Physiological sleep measures predict time to 15‐year mortality in community adults: application of a novel machine learning framework ML Wallace, TS Coleman, LK Mentch, DJ Buysse, JL Graves, EW Hagen, ... Journal of sleep research 30 (6), e13386, 2021 | 20 | 2021 |
| V-statistics and variance estimation Z Zhou, L Mentch, G Hooker Journal of Machine Learning Research 22 (287), 1-48, 2021 | 19 | 2021 |
| Bootstrap bias corrections for ensemble methods G Hooker, L Mentch Statistics and Computing 28, 77-86, 2018 | 19 | 2018 |
| Asymptotic distributions and rates of convergence for random forests via generalized U-statistics W Peng, T Coleman, L Mentch arXiv preprint arXiv:1905.10651, 2019 | 18 | 2019 |
| Asymptotic distributions and rates of convergence for random forests and other resampled ensemble learners W Peng, T Coleman, L Mentch arXiv preprint arXiv:1905.10651, 2019 | 18 | 2019 |
| On racial disparities in recent fatal police shootings L Mentch Statistics and Public Policy 7 (1), 9-18, 2020 | 17 | 2020 |
Giles HookerProfessor of Statistics, University of PennsylvaniaVerified email at wharton.upenn.edu
