Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat: recall and F1-score metrics for classification #277

Merged
merged 10 commits into from
May 5, 2023

Conversation

PhilipGutberlet
Copy link
Contributor

Closes #187.
Closes #186 .

Summary of Changes

Added recall and F1-score functions to the _classifier.

Co-authered-by: [email protected]

@PhilipGutberlet PhilipGutberlet requested a review from a team as a code owner May 5, 2023 13:03
@PhilipGutberlet PhilipGutberlet linked an issue May 5, 2023 that may be closed by this pull request
@lars-reimann
Copy link
Member

lars-reimann commented May 5, 2023

🦙 MegaLinter status: ✅ SUCCESS

Descriptor Linter Files Fixed Errors Elapsed time
✅ PYTHON black 2 0 0 0.68s
✅ PYTHON mypy 2 0 1.67s
✅ PYTHON ruff 2 0 0 0.04s
✅ REPOSITORY git_diff yes no 0.02s

See detailed report in MegaLinter reports
Set VALIDATE_ALL_CODEBASE: true in mega-linter.yml to validate all sources, not only the diff

MegaLinter is graciously provided by OX Security

@lars-reimann lars-reimann changed the title feat: 187 recall metric for classification and 186 F1-score metric for classification feat: recall and F1-socre metrics for classification May 5, 2023
@lars-reimann lars-reimann changed the title feat: recall and F1-socre metrics for classification feat: recall and F1-score metrics for classification May 5, 2023
@codecov
Copy link

codecov bot commented May 5, 2023

Codecov Report

Merging #277 (3879f33) into main (766f2ff) will increase coverage by 0.01%.
The diff coverage is 100.00%.

❗ Current head 3879f33 differs from pull request most recent head cf554b9. Consider uploading reports for the commit cf554b9 to get more accurate results

@@            Coverage Diff             @@
##             main     #277      +/-   ##
==========================================
+ Coverage   99.25%   99.27%   +0.01%     
==========================================
  Files          44       44              
  Lines        1621     1656      +35     
==========================================
+ Hits         1609     1644      +35     
  Misses         12       12              
Impacted Files Coverage Δ
.../safeds/ml/classical/classification/_classifier.py 100.00% <100.00%> (ø)

@lars-reimann lars-reimann enabled auto-merge (squash) May 5, 2023 13:36
@lars-reimann lars-reimann merged commit 2cf93cc into main May 5, 2023
@lars-reimann lars-reimann deleted the 187-recall-metric-for-classification branch May 5, 2023 13:37
lars-reimann pushed a commit that referenced this pull request May 11, 2023
## [0.12.0](v0.11.0...v0.12.0) (2023-05-11)

### Features

* add `learning_rate` to AdaBoost classifier and regressor. ([#251](#251)) ([7f74440](7f74440)), closes [#167](#167)
* add alpha parameter to `lasso_regression` ([#232](#232)) ([b5050b9](b5050b9)), closes [#163](#163)
* add parameter `lasso_ratio` to `ElasticNetRegression` ([#237](#237)) ([4a1a736](4a1a736)), closes [#166](#166)
* Add parameter `number_of_tree` to `RandomForest` classifier and regressor ([#230](#230)) ([414336a](414336a)), closes [#161](#161)
* Added `Table.plot_boxplots` to plot a boxplot for each numerical column in the table ([#254](#254)) ([0203a0c](0203a0c)), closes [#156](#156) [#239](#239)
* Added `Table.plot_histograms` to plot a histogram for each column in the table ([#252](#252)) ([e27d410](e27d410)), closes [#157](#157)
* Added `Table.transform_table` method which returns the transformed Table ([#229](#229)) ([0a9ce72](0a9ce72)), closes [#110](#110)
* Added alpha parameter to `RidgeRegression` ([#231](#231)) ([1ddc948](1ddc948)), closes [#164](#164)
* Added Column#transform ([#270](#270)) ([40fb756](40fb756)), closes [#255](#255)
* Added method `Table.inverse_transform_table` which returns the original table ([#227](#227)) ([846bf23](846bf23)), closes [#111](#111)
* Added parameter `c` to `SupportVectorMachines` ([#267](#267)) ([a88eb8b](a88eb8b)), closes [#169](#169)
* Added parameter `maximum_number_of_learner` and `learner` to `AdaBoost` ([#269](#269)) ([bb5a07e](bb5a07e)), closes [#171](#171) [#173](#173)
* Added parameter `number_of_trees` to `GradientBoosting` ([#268](#268)) ([766f2ff](766f2ff)), closes [#170](#170)
* Allow arguments of type pathlib.Path for file I/O methods ([#228](#228)) ([2b58c82](2b58c82)), closes [#146](#146)
* convert `Schema` to `dict` and format it nicely in a notebook ([#244](#244)) ([ad1cac5](ad1cac5)), closes [#151](#151)
* Convert between Excel file and `Table` ([#233](#233)) ([0d7a998](0d7a998)), closes [#138](#138) [#139](#139)
* convert containers for tabular data to HTML ([#243](#243)) ([683c279](683c279)), closes [#140](#140)
* make `Column` a subclass of `Sequence` ([#245](#245)) ([a35b943](a35b943))
* mark optional hyperparameters as keyword only ([#296](#296)) ([44a41eb](44a41eb)), closes [#278](#278)
* move exceptions back to common package ([#295](#295)) ([a91172c](a91172c)), closes [#177](#177) [#262](#262)
* precision metric for classification ([#272](#272)) ([5adadad](5adadad)), closes [#185](#185)
* Raise error if an untagged table is used instead of a `TaggedTable` ([#234](#234)) ([8eea3dd](8eea3dd)), closes [#192](#192)
* recall and F1-score metrics for classification ([#277](#277)) ([2cf93cc](2cf93cc)), closes [#187](#187) [#186](#186)
* replace prefix `n` with `number_of` ([#250](#250)) ([f4f44a6](f4f44a6)), closes [#171](#171)
* set `alpha` parameter for regularization of `ElasticNetRegression` ([#238](#238)) ([e642d1d](e642d1d)), closes [#165](#165)
* Set `column_names` in `fit` methods of table transformers to be required ([#225](#225)) ([2856296](2856296)), closes [#179](#179)
* set learning rate of Gradient Boosting models ([#253](#253)) ([9ffaf55](9ffaf55)), closes [#168](#168)
* Support vector machine for regression and for classification ([#236](#236)) ([7f6c3bd](7f6c3bd)), closes [#154](#154)
* usable constructor for `Table` ([#294](#294)) ([56a1fc4](56a1fc4)), closes [#266](#266)
* usable constructor for `TaggedTable` ([#299](#299)) ([01c3ad9](01c3ad9)), closes [#293](#293)

### Bug Fixes

* OneHotEncoder no longer creates duplicate column names ([#271](#271)) ([f604666](f604666)), closes [#201](#201)
* selectively ignore one warning instead of all warnings ([#235](#235)) ([3aad07d](3aad07d))
@lars-reimann
Copy link
Member

🎉 This PR is included in version 0.12.0 🎉

The release is available on:

Your semantic-release bot 📦🚀

@lars-reimann lars-reimann added the released Included in a release label May 11, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
released Included in a release
Projects
None yet
Development

Successfully merging this pull request may close these issues.

Recall metric for classification F1 score metric for classification
3 participants