postprocess: Postprocess parboost ensemble components
In parboost: Distributed Model-Based Boosting
Description
Usage
Arguments
Details
Value
Author(s)
Description
Postprocess the submodels
Usage
1
2
postprocess(response, family, list_of_models, postprocessing,
cores_cv = detectCores())
Arguments
response
The response vector.
family
Boosting family.
list_of_models
List of submodels.
postprocessing
Type of postprocessing.
Details
Either euqally weigh all submodels or perform (penalized) regression
on them to determine the weights.
Value
Predictions of postprocessed ensemble and a list of mboost models
Author(s)
Ronert Obst
parboost documentation built on May 2, 2019, 5:08 a.m.
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Description Usage Arguments Details Value Author(s)
Description
Postprocess the submodels
Usage
1 2 | postprocess(response, family, list_of_models, postprocessing,
cores_cv = detectCores())
|
Arguments
response |
The response vector. |
family |
Boosting family. |
list_of_models |
List of submodels. |
postprocessing |
Type of postprocessing. |
Details
Either euqally weigh all submodels or perform (penalized) regression on them to determine the weights.
Value
Predictions of postprocessed ensemble and a list of mboost models
Author(s)
Ronert Obst
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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