These are data used to generate the results presented in simulation studies conducted in Fouodo et al. 2023. Each dataset is an R object in RDS format with 100 lists. For each element of the list, parameters used to generate the data are presented, followed by the simulated data. Here is the git repository of the R code used to conduct simulations in the manuscript. The files 01-data-only.R and 02-data-only.R contain the functions and more details about how the data have been simulated for studies 1 and 2
This repository includes the data files for the simulation study and the case study in the publicati...
Recent studies have expanded the focus of machine learning methods like random forests beyond predic...
Variable importance measures for random forests have been receiving increased attention as a means o...
This book offers an application-oriented guide to random forests: a statistical learning method exte...
This book offers an application-oriented guide to random forests: a statistical learning method exte...
International audienceThis paper describes the R package VSURF. Based on random forests, and for bot...
In this paper we present our work on the Random Forest (RF) family of classification methods. Our go...
Random Forests (RF) of tree classifiers are a popular ensemble method for classification. RF have sh...
See readme.txt for a description of the files in this repository.This repository contains data and R...
<p>These files represent the source code and technical fitting details of the Random Forest-based po...
Simulation studies allow researchers to answer specific questions about data analysis, statistical p...
R-code used for all tree and phenotypic data simulations, and for fitting different models to the si...
RF_BOTH.RData is the Random Forest model that was generated for predicting VIWTP habitat suitability
A major focus in statistics is building and improving computational algorithms that can use data to ...
Input variables used by the Random Forests for the estimation of the direct economic impacts and the...
This repository includes the data files for the simulation study and the case study in the publicati...
Recent studies have expanded the focus of machine learning methods like random forests beyond predic...
Variable importance measures for random forests have been receiving increased attention as a means o...
This book offers an application-oriented guide to random forests: a statistical learning method exte...
This book offers an application-oriented guide to random forests: a statistical learning method exte...
International audienceThis paper describes the R package VSURF. Based on random forests, and for bot...
In this paper we present our work on the Random Forest (RF) family of classification methods. Our go...
Random Forests (RF) of tree classifiers are a popular ensemble method for classification. RF have sh...
See readme.txt for a description of the files in this repository.This repository contains data and R...
<p>These files represent the source code and technical fitting details of the Random Forest-based po...
Simulation studies allow researchers to answer specific questions about data analysis, statistical p...
R-code used for all tree and phenotypic data simulations, and for fitting different models to the si...
RF_BOTH.RData is the Random Forest model that was generated for predicting VIWTP habitat suitability
A major focus in statistics is building and improving computational algorithms that can use data to ...
Input variables used by the Random Forests for the estimation of the direct economic impacts and the...
This repository includes the data files for the simulation study and the case study in the publicati...
Recent studies have expanded the focus of machine learning methods like random forests beyond predic...
Variable importance measures for random forests have been receiving increased attention as a means o...