mlr3pipelines
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PipeOp that constructs a data-dependent Graph and runs it
The user gives a function as parameter that takes a task and returns a Graph. That graph is then trained on the training data and the trained Graph is used for prediction.
Some notes:
- probably not just a PipeOpTaskPreproc, but a whole PipeOp, with construction argument: number of input channels (default vararg), number of output channels (default 1)
- parameter function is called with do.call, so user doesn't need to bother with list access
- Difficulty here is that cloning gets a bit difficult maybe?