Ensembling: provide original input data as features to metalearner
Offen
enhancement
needs design
performance
spike
- Vorherrschende Sprache
- Python
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- 850
- Forks
- 96
- PR-Merge-Kennzahlen
- Keine gemergten PRs in 30 T.
Beschreibung
**Background**
Currently our ensembler components are provided as features only the predictions or predicted probabilities from the input pipelines.
**Proposal**
Alongside the input pipeline predictions or predicted probabilities, include a preprocessing chain which additionally provides the processed input features to the metalearner.
Our new automl algo first constructs a preprocessing chain, then applies that same chain to each estimator. We should use the same chain as input to the metalearner.
Filed as a spike because we should agree on the design before merging any code which changes the behavior of automl.
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