Comments (2)
Most PipeOps operate on feature columns. They sometimes take the values of the target column into account where it makes sense (e.g. PipeOpSubsample
can do stratified sampling and therefore needs target values).
Other column roles are very rarely used or modified. I don't think there is any pipeop that takes the weights column into account (PipeOpScale
from your question does not), and only few PipeOps can modify the weights (PipeOpClassWeights
and PipeOpColRoles
). There are also a few others that operate on the target column.
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Thank you, the detailed response is much appreciated :)
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Related Issues (20)
- Classbalancing pipe operator when used with resample HOT 3
- .result for train / test separately, or for resampling instances
- pipeop$predict_newdata() functionality
- Graph should support in-place operations
- `PipeOpUpdateTarget` doesn't work for survival tasks with 2 target columns
- use encapsulate
- PipeOpFeatureUnion drops columns names "x" HOT 1
- Change id of "featureunion"either "stacking" or "robustifuy" ppl to make example in the book work.
- crate all custom_check functions HOT 1
- $add_pipeop() should have 'clone' argument. HOT 1
- Typo in documentation for `ppl()` HOT 1
- dependencies in PSCs
- Allow other packages to use mlr3pipelines test helpers HOT 1
- `PipeOpEncode` doesn't work for features of type `character()` HOT 2
- strange error messages in online doc
- Support for UMAP: Uniform Manifold Approximation and Projection
- Support for tSNE: t-Distributed Stochastic Neighbour Embeddings
- Support for metric MDS
- mice package
- FIXMEs in `PipeOpTaskPreproc`
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