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Remove error "Dataset already contains the target column" when predicting #636

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lars-reimann opened this issue Apr 22, 2024 · 1 comment · Fixed by #687
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Remove error "Dataset already contains the target column" when predicting #636

lars-reimann opened this issue Apr 22, 2024 · 1 comment · Fixed by #687
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enhancement 💡 New feature or request released Included in a release

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@lars-reimann
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Is your feature request related to a problem?

Functions that compute metrics of a classifier/regressor expect a tagged table. predict specifically forbids tables that include the target column already, so also a tagged table.

Desired solution

Don't raise an error in predict if the input already has the target. Simply overwrite the target column instead.

Possible alternatives (optional)

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@lars-reimann lars-reimann added the enhancement 💡 New feature or request label Apr 22, 2024
@lars-reimann lars-reimann self-assigned this May 1, 2024
@lars-reimann lars-reimann linked a pull request May 1, 2024 that will close this issue
feat: allow using tables that already contain target for prediction #687
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@lars-reimann lars-reimann mentioned this issue May 1, 2024
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lars-reimann added a commit that referenced this issue May 1, 2024
@lars-reimann
feat: allow using tables that already contain target for prediction (#…
e9f1cfb 
…687)

Closes #636

### Summary of Changes

No longer raise an error if a table that already contains the target is
passed to `predict`. It's now simply ignored for training and
overwritten.
lars-reimann pushed a commit that referenced this issue May 1, 2024
@semantic-release-bot
chore(release): 0.22.0 [skip ci]
43717e0 
## [0.22.0](v0.21.0...v0.22.0) (2024-05-01)

### Features

* `is_fitted` is now always a property ([#662](#662)) ([b1db881](b1db881)), closes [#586](#586)
* add `Column.missing_value_count` ([#682](#682)) ([f084916](f084916)), closes [#642](#642)
* Add `InputConversion` & `OutputConversion` for nn interface ([#625](#625)) ([fd723f7](fd723f7)), closes [#621](#621)
* Add hash,eq and sizeof in ForwardLayer ([#634](#634)) ([72f7fde](72f7fde)), closes [#633](#633)
* allow using tables that already contain target for prediction ([#687](#687)) ([e9f1cfb](e9f1cfb)), closes [#636](#636)
* callback `Row.sort_columns` takes four parameters instead of two tuples ([#683](#683)) ([9c3e3de](9c3e3de)), closes [#584](#584)
* rename `group_rows_by` in `Table` to `group_rows` ([#661](#661)) ([c1644b7](c1644b7)), closes [#611](#611)
* rename `number_of_column` in `Row` to `number_of_columns` ([#660](#660)) ([0a08296](0a08296)), closes [#646](#646)
* rework `TaggedTable` ([#680](#680)) ([db2b613](db2b613)), closes [#647](#647)
* show missing value count/ratio in summarized statistics ([#684](#684)) ([74b8a35](74b8a35)), closes [#619](#619)
* specify `extras` instead of `features` in `to_tabular_dataset` ([#685](#685)) ([841657f](841657f)), closes [#623](#623)

### Bug Fixes

* actually use `kernel` of support vector machines for training ([#681](#681)) ([09c5082](09c5082)), closes [#602](#602)

### Performance Improvements

* Faster plot_histograms and more reliable plots ([#659](#659)) ([b5f0a12](b5f0a12))
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🎉 This issue has been resolved in version 0.22.0 🎉

The release is available on:

Your semantic-release bot 📦🚀

@lars-reimann lars-reimann added the released Included in a release label May 1, 2024
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feat: allow using tables that already contain target for prediction Safe-DS/Library
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