Random-Splitting Random Forest with Multiple Mixed-Data Covariates

Random-Splitting Random Forest with Multiple Mixed-Data Covariates

Background: The bagging (BG) and random forest (RF) are famous supervised statistical learning methods based on classification and regression trees. The BG and RF can deal with different types of responses such as categorical, continuous, etc. There are curves, time series, functional data, or obse...

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Bibliographic Details
Main Authors: Mohammad Fayaz, Alireza Abadi, Soheila Khodakarimd
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2023-03-01
Series:Journal of Biostatistics and Epidemiology
Subjects:
Bagging
Functional data
Random forest
Random splitting
Statistical learning
Online Access:https://jbe.tums.ac.ir/index.php/jbe/article/view/1071

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