Year: 2009
Type: dissertation
Abstract: In this talk we will discuss classification and regression trees as statistical learners, particularly their use as part of an ensemble. We will discuss the increasing role that randomness has played in developing new tree ensemble techniques. Specifically, it has remained somewhat unclear as to why the simple act of randomizing the tree growing algorithm should lead to the dramatic improvements in performance that have been observed. We will introduce the recent suggestion that a specific type of tree ensemble acts by forming a locally adaptive distance metric as a possible explanation and briefly outline a generalization of this claim to include all tree ensemble methods.
Source: The Mathematics Enthusiast
Author: Joran Elias
Institution: University of Montana
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W822979023