📣 🥁 Changelog & Releases#

📍 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#

🔥 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