Check table for invalid values when fitting #655
Labels
Comments
sibre28
added a commit
that referenced
this issue
Jun 11, 2024
Closes #655 ### Summary of Changes Add InvalidFitDataError and tests --------- Co-authored-by: megalinter-bot <129584137+megalinter-bot@users.noreply.github.com>
lars-reimann
pushed a commit
that referenced
this issue
Jul 19, 2024
## [0.27.0](v0.26.0...v0.27.0) (2024-07-19) ### Features * join ([#870](#870)) ([5764441](5764441)), closes [#745](#745) * activation function for forward layer ([#891](#891)) ([5b5bb3f](5b5bb3f)), closes [#889](#889) * add `ImageDataset.split` ([#846](#846)) ([3878751](3878751)), closes [#831](#831) * add FunctionalTableTransformer ([#901](#901)) ([37905be](37905be)), closes [#858](#858) * add InvalidFitDataError ([#824](#824)) ([487854c](487854c)), closes [#655](#655) * add KNearestNeighborsImputer ([#864](#864)) ([fcdfecf](fcdfecf)), closes [#743](#743) * add moving average plot ([#836](#836)) ([abcf68a](abcf68a)) * add RobustScaler ([#874](#874)) ([62320a3](62320a3)), closes [#650](#650) [#873](#873) * add SequentialTableTransformer ([#893](#893)) ([e93299f](e93299f)), closes [#802](#802) * add temporal operations ([#832](#832)) ([06eab77](06eab77)) * added 'histogram_2d' in TablePlotter ([#903](#903)) ([4e65ba9](4e65ba9)), closes [#869](#869) [#798](#798) * added from_str_to_temporal and continues prediction ([#767](#767)) ([35f468a](35f468a)), closes [#806](#806) [#765](#765) [#740](#740) [#773](#773) * added GRU layer ([#845](#845)) ([d33cb5d](d33cb5d)) * Adds Dropout Layer ([#868](#868)) ([a76f0a1](a76f0a1)), closes [#848](#848) * dark mode for plots ([#911](#911)) ([5447551](5447551)), closes [#798](#798) * easily create a baseline model ([#811](#811)) ([8e1b995](8e1b995)), closes [#710](#710) * get first cell with value other than `None` ([#904](#904)) ([5a0cdb3](5a0cdb3)), closes [#799](#799) * hyperparameter optimization for fnn models ([#897](#897)) ([c1f66e5](c1f66e5)), closes [#861](#861) * implement violin plots ([#900](#900)) ([9f5992a](9f5992a)), closes [#867](#867) * plot decision tree ([#876](#876)) ([d3f81dc](d3f81dc)), closes [#856](#856) * prediction no longer takes a time series dataset only table ([#838](#838)) ([762e5c2](762e5c2)), closes [#837](#837) * raise if `remove_colums` is called with unknown column by default ([#852](#852)) ([8f78163](8f78163)), closes [#807](#807) * regularization strength for logistic classifier ([#866](#866)) ([9f74e92](9f74e92)), closes [#750](#750) * reorders parameters of RangeScaler and makes them keyword-only ([#847](#847)) ([2b82db7](2b82db7)), closes [#809](#809) * replace seaborn with matplotlib for box_plot ([#863](#863)) ([4ef078e](4ef078e)), closes [#805](#805) [#849](#849) * replaced seaborn with matplotlib for correlation_heatmap ([#850](#850)) ([d4680d4](d4680d4)), closes [#800](#800) [#849](#849) ### Bug Fixes * **deps:** bump urllib3 from 2.2.1 to 2.2.2 ([#842](#842)) ([b81bcd6](b81bcd6)), closes [#3122](https://github.com/Safe-DS/Library/issues/3122) [#3363](https://github.com/Safe-DS/Library/issues/3363) [#3122](https://github.com/Safe-DS/Library/issues/3122) [#3363](https://github.com/Safe-DS/Library/issues/3363) [#3406](https://github.com/Safe-DS/Library/issues/3406) [#3398](https://github.com/Safe-DS/Library/issues/3398) [#3399](https://github.com/Safe-DS/Library/issues/3399) [#3396](https://github.com/Safe-DS/Library/issues/3396) [#3394](https://github.com/Safe-DS/Library/issues/3394) [#3391](https://github.com/Safe-DS/Library/issues/3391) [#3316](https://github.com/Safe-DS/Library/issues/3316) [#3387](https://github.com/Safe-DS/Library/issues/3387) [#3386](https://github.com/Safe-DS/Library/issues/3386) * labels of correlation heatmap ([#894](#894)) ([a88a609](a88a609)), closes [#871](#871) * make multi-processing in baseline models more consistent ([#909](#909)) ([fa24560](fa24560)), closes [#907](#907) ### Performance Improvements * improved performance in various methods in `Image` and `ImageList` ([#879](#879)) ([134e7d8](134e7d8))
|
🎉 This issue has been resolved in version 0.27.0 🎉 The release is available on:
Your semantic-release bot 📦🚀 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Is your feature request related to a problem?
When fitting a model, passing a table containing missing values or non-numerical data will result in either a numpy error or in all future predictions of the model being NaN.
Desired solution
In the InputConversionLayer, check the passed table for invalid data and throw a clear error if so.
Possible alternatives (optional)
No response
Screenshots (optional)
No response
Additional Context (optional)
No response
The text was updated successfully, but these errors were encountered: