bm_randomforest {tsensembler} | R Documentation |
Fit Random Forest models
Description
Learning a Random Forest Model from training data. Parameter setting can vary in num.trees and mtry parameters.
Usage
bm_randomforest(form, data, lpars)
Arguments
form |
formula |
data |
training data for building the predictive model |
lpars |
a list containing the learning parameters |
Details
See ranger
for a comprehensive description.
Imports learning procedure from ranger package.
See Also
other learning models: bm_mars
;
bm_ppr
; bm_gbm
;
bm_glm
; bm_cubist
;
bm_gaussianprocess
; bm_pls_pcr
;
bm_ffnn
; bm_svr
Other base learning models:
bm_cubist()
,
bm_ffnn()
,
bm_gaussianprocess()
,
bm_gbm()
,
bm_glm()
,
bm_mars()
,
bm_pls_pcr()
,
bm_ppr()
,
bm_svr()
[Package tsensembler version 0.1.0 Index]