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Create realistic use cases for the package #273

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sebffischer opened this issue Aug 21, 2024 · 0 comments

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sebffischer commented Aug 21, 2024 •

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think of some use-cases
- simple use case: xgboost vs torch: no factors, no missing values
- xgboost vs deep learning: use datasets from openml and benchmark them.
  with missing values and factor variables
- proper benchmark: tuning, maybe batchmark, internal tuning
- try to fit an image dataset:
  - using a pretrained network
  - no pretrained network.
  - with data augmentation

sebffischer changed the title ~~Check That package works~~ Create realistic use cases for the package

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