RandomForestModel {MachineShop} | R Documentation |
Implementation of Breiman's random forest algorithm (based on Breiman and Cutler's original Fortran code) for classification and regression.
RandomForestModel( ntree = 500, mtry = .(if (is.factor(y)) floor(sqrt(nvars)) else max(floor(nvars/3), 1)), replace = TRUE, nodesize = .(if (is.factor(y)) 1 else 5), maxnodes = NULL )
ntree |
number of trees to grow. |
mtry |
number of variables randomly sampled as candidates at each split. |
replace |
should sampling of cases be done with or without replacement? |
nodesize |
minimum size of terminal nodes. |
maxnodes |
maximum number of terminal nodes trees in the forest can have. |
factor
, numeric
mtry
, nodesize
*
* included only in randomly sampled grid points
Default values for the NULL
arguments and further model details can be
found in the source link below.
MLModel
class object.
## Requires prior installation of suggested package randomForest to run fit(sale_amount ~ ., data = ICHomes, model = RandomForestModel)