mlr3pipelines

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support marshaling in GraphLearner

1

~~still missing some tests, news, docs~~

sebffischer

m-muecke

Support for metric MDS

2

Implentation: `stats::cmdscale`

m-muecke

Implementation can be found in the `Rtsne` package https://github.com/jkrijthe/Rtsne. But there is no transform/predict method available, see the discussion here https://github.com/jkrijthe/Rtsne/issues/6 and from the [FAQ](https://lvdmaaten.github.io/tsne/#faq): > "Once I have a...

m-muecke

predict on test set rows

4

go through each pipeop and let it predict directly, since some pipeops need the predicted set

mb706

sebffischer

We should not need this: https://github.com/mlr-org/mlr3book/blob/b16a689e4a93b8f5e1b6957c1e63f16ec8f8f6ae/book/chapters/appendices/solutions.qmd#L1324-L1329 see also https://mlr-org.com/gallery/optimization/2021-03-11-practical-tuning-series-build-an-automated-machine-learning-system/ Maybe we can also avoid needing to declare dependencies here: https://github.com/mlr-org/mlr3book/blob/b16a689e4a93b8f5e1b6957c1e63f16ec8f8f6ae/book/chapters/appendices/solutions.qmd#L1300-L1318

mb706

sebffischer

mb706

https://mlr3pipelines.mlr-org.com/reference/po.html !

bblodfon