<p>Permutation-based variable importance measures for each predictor derived from multiple random forest runs for a) all mosaics b) Nilgiris and Eravikulam plateaus (> 1500m elevation). Please refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130566#pone.0130566.t001" target="_blank">Table 1</a> for explanation of predictor codes.</p
Background: Variable importance measures for random forests have been receiving increased attention ...
The random forest (RF) method is a commonly used tool for classi-fication with high dimensional data...
<p>Results shown treat parameters as continuous variables. Results were similar when parameters were...
Background: Random forests are becoming increasingly popular in many scientific fields because they ...
<p>Included variables are listed on the vertical axis, with corresponding variable importance for ea...
A major focus in statistics is building and improving computational algorithms that can use data to ...
Dots represent the mean cross-entropy loss for a given variable for 50 permuted samples for the obse...
Background Random forests are a popular method in many fields since they can be successfully appl...
The box and violin plots display the distribution of cross-entropy loss for a given variable for 50 ...
This paper is about variable selection with the random forests algorithm in presence of correlated p...
Data analysis and machine learning have become an integrative part of the modern scientific methodol...
BACKGROUND: Random forest based variable importance measures have become popular tools for assessing...
Random forests are becoming increasingly popular in many scientific fields because they can cope wit...
Variable importance measures for random forests have been receiving increased attention as a means o...
Variable importance measures for random forests have been receiving increased attention as a means o...
Background: Variable importance measures for random forests have been receiving increased attention ...
The random forest (RF) method is a commonly used tool for classi-fication with high dimensional data...
<p>Results shown treat parameters as continuous variables. Results were similar when parameters were...
Background: Random forests are becoming increasingly popular in many scientific fields because they ...
<p>Included variables are listed on the vertical axis, with corresponding variable importance for ea...
A major focus in statistics is building and improving computational algorithms that can use data to ...
Dots represent the mean cross-entropy loss for a given variable for 50 permuted samples for the obse...
Background Random forests are a popular method in many fields since they can be successfully appl...
The box and violin plots display the distribution of cross-entropy loss for a given variable for 50 ...
This paper is about variable selection with the random forests algorithm in presence of correlated p...
Data analysis and machine learning have become an integrative part of the modern scientific methodol...
BACKGROUND: Random forest based variable importance measures have become popular tools for assessing...
Random forests are becoming increasingly popular in many scientific fields because they can cope wit...
Variable importance measures for random forests have been receiving increased attention as a means o...
Variable importance measures for random forests have been receiving increased attention as a means o...
Background: Variable importance measures for random forests have been receiving increased attention ...
The random forest (RF) method is a commonly used tool for classi-fication with high dimensional data...
<p>Results shown treat parameters as continuous variables. Results were similar when parameters were...