AI Chat AI Image Generator AI Video Text to Speech

A note on the consistency of the random forest algorithm

10/02/2019

∙

by José A. Ferreira, et al.

∙

∙

Examples are given of data-generating models for which Breiman's random forest algorithm does not yield consistent statistical predictors.

page 1

page 2

page 3

page 4

research

∙ 11/28/2022

Data-driven multinomial random forest

In this paper, we strengthen the previous weak consistency proof method ...

0 JunHao Chen, et al. ∙

research

∙ 04/18/2018

Exact Distributed Training: Random Forest with Billions of Examples

We introduce an exact distributed algorithm to train Random Forest model...

0 Mathieu Guillame-Bert, et al. ∙

research

∙ 11/10/2020

On the consistency of a random forest algorithm in the presence of missing entries

This paper tackles the problem of constructing a non-parametric predicto...

0 Irving Gómez Méndez, et al. ∙

research

∙ 04/29/2020

Asymptotic Properties of High-Dimensional Random Forests

As a flexible nonparametric learning tool, random forest has been widely...

0 Chien-Ming Chi, et al. ∙

research

∙ 12/15/2018

Consistent Estimation of Residual Variance with Random Forest Out-Of-Bag Errors

The issue of estimating residual variance in regression models has exper...

0 Burim Ramosaj, et al. ∙

research

∙ 12/14/2018

Making Sense of Random Forest Probabilities: a Kernel Perspective

A random forest is a popular tool for estimating probabilities in machin...

0 Matthew A. Olson, et al. ∙

research

∙ 01/29/2022

Geometry- and Accuracy-Preserving Random Forest Proximities

Random forests are considered one of the best out-of-the-box classificat...

8 Jake S. Rhodes, et al. ∙