Currently mlr supports observation weights for a task. In situations when the observation weights could change in resampling training instances (time series) it would be beneficial to extend the ResamplingCustom function to accommodate this. An extension for custom observation weights, class weights and class costs is general and gives the user the ability to use the mlr3 framework in more ways.
There is a forecasting extension for mlr3, but this proposal does not collide with that extension.
I have created a pull request with the suggested extension. It is my first pull request ever so please excuse any errors and deviations from good practice. Mistakes will be of course corrected.
Mlr used wrappers for extending learners and tasks. It would be necessary to create some wrappers to be used after custom weights resampling. What is the plan for mlr3 in this regard? In case this proposal is accepted I could try to make such wrapper.
mllg
commented
5 years ago
Currently mlr supports observation weights for a task. In situations when the observation weights could change in resampling training instances (time series) it would be beneficial to extend the ResamplingCustom function to accommodate this. An extension for custom observation weights, class weights and class costs is general and gives the user the ability to use the mlr3 framework in more ways.
There is a forecasting extension for mlr3, but this proposal does not collide with that extension.
I have created a pull request with the suggested extension. It is my first pull request ever so please excuse any errors and deviations from good practice. Mistakes will be of course corrected.
Mlr used wrappers for extending learners and tasks. It would be necessary to create some wrappers to be used after custom weights resampling. What is the plan for mlr3 in this regard? In case this proposal is accepted I could try to make such wrapper.