📣 🥁 Changelog & Releases

We follow Semantic Versioning to document any notable changes.
Please checkout SlickML Official Releases for more details.

📍 Unreleased Version X.X.X - XXXX-XX-XX

🛠 Fixed

🔥 Added

📍 Version 0.2.1 - 2022-12-29

🛠 Fixed

#174 fixed badges in API docs.

🔥 Added

#177, #176 added CLI basic functionalities for version and help.
#175 added unit-tests to cover save-path flag in all visualization modules.
#173 added threshold in .coveragerc and codecov.yml to protect test coverages.

📍 Version 0.2.0 - 2022-11-27

🛠 Fixed

#170 enabled more flake8 plugins and fixed poe check command and mypy dependencies.
#169 refactored XGBoostHyperOptimizer class.

🔥 Added

#171 added type-stubs and rolled out type checking with mypy across library.

📍 Version 0.2.0-beta.2 - 2022-11-13

🛠 Fixed

#167, #160 fixed dependencies, tox.ini and README.md.
#164 refactored XGBoostBayesianOptimizer class.
#161 fixed XGBoostFeatureSelector callbacks to work smoothly.
#157 fixed codecov-action to use v3.
#156 refactored XGBoostFeatureSelector class.
#155 fixed default PR reviewers.

🔥 Added

#162 added BaseXGBoostEstimator class.
#158 added conftest.py for pytest unit-tests.
#153, #159 added ascii banner arts to poe greet command.

📍 Version 0.2.0-beta.1 - 2022-10-04

🛠 Fixed

#143, #123 fixed CI/CD workflows.
#141, #144 refactored GLMNetCVClassifier.
#137, #135 refactored XGBoostCVRegressor.
#133, #126 refactored XGBoostCVClassifier.
#147, #113, #108, #109 refactored Metrics.
#95, #100, #100 fixed Format / Lint.
#96, #98, #112 fixed Utils functions and transformations.
#105, #150, #148, #145, #114, #127, #115, #129, #130, #117, #116, #111, #124 fixed Sphinx Auto-Api Docs + README.

🔥 Added

#142 added Poetry v1.2 dependencies.
#138 added codecov.yml.
#131 added py.typed to comply with PEP-561.
#104 added Workflow for API Docs Deploy.
#103 added Check-Var Utilities.
#99 added PR template.

📍 Version 0.2.0-beta - 2022-05-29

🛠 Fixed

#78 build badge using GitHub actions and removed the travis-ci badge and dependencies.
#77 updated .flake8, .gitingore entries, ISSUE_TEMPLATES, README.md, CONTRIBUTING.md, assets/, examples/ formats, and src/ style, ci.yml workflow.

🔥 Added

#77 added poetry essentials and essentials based on #72 and removed all setup.py essentials.
#77 added tox, mypy, pytest-cov.
#77 added sphinx-auto-api-doc based on #32.

📍 Version 0.1.5 - 2021-09-06

🛠 Fixed

#74 updated requirements.txt to the latest versions.
#71 updated optimization examples.

🔥 Added

#71 added XGBoostRegressorBayesianOpt and XGBoostRegressorHyperOpt classes in optimization.

📍 Version 0.1.4 - 2021-05-31

🛠 Fixed

#70 fixed bugs in plot_xgb_cv_results.
#70 fixed bugs in plot_regression_metrics.
#70 updated metrics initialization in XGBoostClassifier and XGBoostCVClassifier.
#70 updated notebook examples to go over each class separetely.

🔥 Added

#70 added XGBoostRegressor and XGBoostCVRegressor classes.
#70 added NeurIPS 2021 submission pdf.

📍 Version 0.1.3 - 2021-05-15

🛠 Fixed

#68 updated save_path in plotting functions.
#68 updated bibtex citations to software.
#67 fixed bugs in metrics.
#66 fixed bugs in feature selection algorithm.
#66 updated the order of the functions inside each class.

🔥 Added

#68 added directories for JOSS and NeurIPS papers.

📍 Version 0.1.2 - 2021-04-17

🛠 Fixed

#64 updated setup.py with dynamic version and install requirements
#63 fixed bugs in RegressionMetrics plotting. Now, the text label positions are dynamic and invariat of the data. Additionally, fixed the bug in coef. shapes in GLMNet classes.
#63 updated all docstrings based on Scikit-Learn API
#61 updated metrics.py attributes API to end with under-score

🔥 Added

#63 added GLMNetCVRegressor class
#60 added CHANGELOG.md

📍 Version 0.1.1 - 2021-03-18

🛠 Fixed

#59 updated docstrings
#57 updated requirements.txt
#56 fixed bugs in plotting
#54 fixed bug in XGBoostClassifer. dtest has y_test as required parameter while it should be optional, since you wont have the y_true in production.

🔥 Added

#57 added GLMNetCVClassifier class, plotting, and examples, CODE_OF_CONDUCT.md
#44 added XGBoostClassifierHyperOpt

📍 Version 0.0.8 - 2021-02-17

🛠 Fixed

#52 updated xgboost version to 1.0.0 to remove the conflict with shap version
#47 fixed bugs in HyperOpt __init__

🔥 Added

#52 added SHAP waterfall plot
#51 added regression metrics
#49 added Google Colab links to notebooks
#44 added XGBoostClassifierHyperOpt

📍 Version 0.0.7 - 2020-09-27

🛠 Fixed

#41 updated requirements for bayesian optimization, design pattern, classification examples
#38 fixed typos in README and bug in df_to_csr function
#34 fixed formatting and import bugs in source code
#28 updated feature selection method from run to fit and removed X, y from init and added to fit to be similar to sklearn API.
#17 updated plotting to Matplotlib object oriented API

🔥 Added

#43 added BayesianOpt class
#38 added unit tests for classification
#37 added SHAP summary plots
#24 added XGBoostCVClassifier
#23 added examples for feature selection
#20 added formatting.py
#15 added feature_selection.py and tests/
#12 added PEP8
#9 added plots for metrics and utilities.py
#6 added logo design
#4 added metrics.py

📍 Version 0.0.1 - 2020-08-31

🔥 Added

#2 initial ideas