Performance optimization: memoize/cache fitted components and predictions during automl
オープン
needs design
new feature
performance
spike
- 主要言語
- Python
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- 850
- フォーク
- 96
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説明
A feature evalml could support down the road is the ability to cache the output of each combination of components our pipelines have trained, so that if that component string is used again during automl, its fetched from the cache rather than recomputed.
Sklearn supports this functionality: [see the `memory` parameter on `Pipeline`](https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html), and also [this issue in their repo](https://github.com/scikit-learn/scikit-learn/issues/9007).
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