AutoML Pipeline – Java API

[sebhrusen]

Sub-issue of #15854

Provide pipeline abstraction (Model, ModelBuilder, Transformation, …) encapsulating a sequence of transformations and a final (optional) predictive model.

** Requirements **
Training of the pipeline should support cross-validation without data leakage.
The trained pipeline model must be able to score/predict, including from the clients.

** Notes **
MOJO not yet supported.

The current implementation focuses on the backend implementation: the client support is only here to manipulate—esp. be able to predict—pipeline models that have been built by AutoML for example.
There are many ways to extend the pipeline logic and make it more customizable:

1. in AutoML, the preprocessing param can used to select various predefined transformers that will make up the training pipeline.
2. for single models and grids, the pipeline client can later be extended to allow the user to define its own pipeline (for example using a syntax similar to sklearn Pipeline).
3. for even more ad-hoc customization, like the scenario you're suggesting, we could allow code ingestion—probably jython scripts, it should not be too difficult to implement a JythonDataTransformer.

Finally, let's keep in mind that Mojo support is also not supported yet, although likely to be much easier to support with this Pipeline mechanism than with the legacy Target encoding support embedded in Model/ModelBuilder for example, as every transformation now applies clearly sequentially and the estimator model (e.g. GLM) contains only post-transformation information, whereas with the legacy TE integration the model contained a mix of pre-encoding and post-encoding making the MOJO extremely difficult to implement due to other categorical encoding being mixed to this.