3 papers
stat.ML2022
The Infinitesimal Jackknife and Combinations of Models
Indrayudh Ghosal, Yunzhe Zhou, Giles Hooker
The Infinitesimal Jackknife is a general method for estimating variances of parametric models, and more recently also for some ensemble methods. In this paper we extend the Infinit…
stat.ME2021
Generalised Boosted Forests
Indrayudh Ghosal, Giles Hooker
This paper extends recent work on boosting random forests to model non-Gaussian responses. Given an exponential family our goal is to obtain an est…
stat.ML2018
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and its Variance Estimate
Indrayudh Ghosal, Giles Hooker
In this paper we propose using the principle of boosting to reduce the bias of a random forest prediction in the regression setting. From the original random forest fit we extract…