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feat: hyperparameter optimization for fnn models #897

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merged 42 commits into from
Jul 15, 2024

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@sibre28 sibre28 commented Jul 11, 2024

Closes #861

Summary of Changes

Added fit_by_exhaustive_search method to NNClassifier, NNRegressor
Added FittingWithChoice and FittingWithoutChoice Error
Added Choice options for neuron_count params of all layers
Added contains_choices method to all layers
Added _get_layers_for_all_choices method to all layers
Added ClassifierMetric and RegressorMetric as Enums

fit_by_exhaustive_search currently only works for tables as input, images and timeseries will be added in a later pr

@sibre28 sibre28 linked an issue Jul 11, 2024 that may be closed by this pull request
@sibre28 sibre28 changed the title feat: 861 hyperparameter optimization for nn models 1 feat: 861 hyperparameter optimization for nn models Jul 11, 2024
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Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 97.91%. Comparing base (5447551) to head (7903fad).

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@@            Coverage Diff             @@
##             main     #897      +/-   ##
==========================================
+ Coverage   97.79%   97.91%   +0.11%     
==========================================
  Files         122      122              
  Lines        6659     6892     +233     
==========================================
+ Hits         6512     6748     +236     
+ Misses        147      144       -3     

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@sibre28 sibre28 changed the title feat: 861 hyperparameter optimization for nn models feat: hyperparameter optimization for nn models Jul 11, 2024
@sibre28 sibre28 changed the title feat: hyperparameter optimization for nn models feat: hyperparameter optimization for fnn models Jul 13, 2024
@sibre28 sibre28 merged commit c1f66e5 into main Jul 15, 2024
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@sibre28 sibre28 deleted the 861-hyperparameter-optimization-for-nn-models-1 branch July 15, 2024 14:18
lars-reimann pushed a commit that referenced this pull request 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))
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🎉 This PR is included in version 0.27.0 🎉

The release is available on:

Your semantic-release bot 📦🚀

@lars-reimann lars-reimann added the released Included in a release label Jul 19, 2024
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Hyperparameter Optimization for NN Models
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