vignettes/pkgdown/rforest.Rmd
rforest.Rmd
Estimate a Random Forest
To create a Random Forest, first select the type (i.e., Classification or Regression), response variable, and one or more explanatory variables. Press the Estimate model
button or CTRL-enter
(CMD-enter
on mac) to generate results.
The model can be “tuned” by changing the mtry
, # trees
, Min node size
, and Sample fraction
inputs. The best way to determine the optimal values for these hyper parameters is to use Cross-Validation. In radiant, you can use the cv.rforest
function for this purpose. See the documentation for more information.
Add code to Report > Rmd to (re)create the analysis by clicking the icon on the bottom left of your screen or by pressing ALT-enter
on your keyboard.
For an overview of related R-functions used by Radiant to estimate a neural network model see Model > Neural network.
The key function from the ranger
package used in the rforest
tool is ranger
.