lightGBMRecursive: lightGBMRecursive Wrapper function for LightGBM forecasting...
In jdestefani/ExtendedDFML: Extended Dynamic Factor Machine Learner
Description
Usage
Arguments
Value
View source: R/gradientBoosting.R
Description
lightGBMRecursive
Wrapper function for LightGBM forecasting technique with recursive multistep ahead technique
Usage
1
lightGBMRecursive(ts_embed, horizon, params = NULL)
Arguments
ts_embed
Embedded time series, in the inp,out format of gbcode::makeEmbedded
horizon
Forecasting horizon
params
Additional (optional) parameters for LightGBM
Value
h-step forecast of ts_embed using lightGBM and recursive multistep-ahead forecasting technique
jdestefani/ExtendedDFML documentation built on Dec. 20, 2021, 10:04 p.m.
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Description Usage Arguments Value
View source: R/gradientBoosting.R
Description
lightGBMRecursive
Wrapper function for LightGBM forecasting technique with recursive multistep ahead technique
Usage
1 | lightGBMRecursive(ts_embed, horizon, params = NULL)
|
Arguments
ts_embed |
|
horizon |
|
params |
|
Value
h-step forecast of ts_embed using lightGBM and recursive multistep-ahead forecasting technique
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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