Fuzzy Forests: Extending Random Forest Feature Selection for Correlated, High-Dimensional Data

Fuzzy Forests: Extending Random Forest Feature Selection for Correlated, High-Dimensional Data

In this paper we introduce fuzzy forests, a novel machine learning algorithm for ranking the importance of features in high-dimensional classification and regression problems. Fuzzy forests is specifically designed to provide relatively unbiased rankings of variable importance in the presence of hig...

Full description

Bibliographic Details
Main Authors: Daniel Conn, Tuck Ngun, Gang Li, Christina M. Ramirez
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2019-10-01
Series:Journal of Statistical Software
Subjects:
random forests
wgcna
machine learning
r
networks
p >> n
big data
variable selection
variable importance
variable ranking
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/2541

Similar Items

Similar Items