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