saveRF {CORElearn} | R Documentation |
saveRF
: the internal structure of given random forests model is saved to file.
loadRF
: the internal structure of random forests model is loaded from given file and a model is created and returned.
saveRF(model, fileName) loadRF(formula, data, fileName)
model |
The model structure as returned by CoreModel . |
fileName |
Name of the file to save/load the model to/from. |
formula |
Formula shell match the model loaded from file. |
data |
Data shell match the formula and the model loaded from file. |
The function saveRF
saves the internal structure of given random forests model to specified file.
The model
must be a valid structure returned by CoreModel
.
The function loadRF
loads the internal structure of random forests saved in a specified file and
returns access to it in the model
. The parameters formula
and data
have to match
the loaded model, and are needed for subsequent predictions with the loaded model.
saveRF
does not return any value, while loadRF
returns a loaded model as a list, similarly to CoreModel
.
Marko Robnik-Sikonja, Petr Savicky
# use iris data set # build random forests model with certain parameters modelRF <- CoreModel(Species ~ ., iris, model="rf", selectionEstimator="MDL",minNodeWeight=5,rfNoTrees=100) print(modelRF) # prediction with node distribution pred <- predict.CoreModel(modelRF, iris, rfPredictClass=FALSE, type="both") print(pred) # saves the random forests model to file saveRF(modelRF, "tempRF.txt") # restore the model to another model loadedRF = loadRF(Species ~ ., iris, "tempRF.txt") # prediction should be the same predLoaded <- predict.CoreModel(loadedRF, iris, rfPredictClass=FALSE, type="both") print(predLoaded)