**AgeML 0.2.0** available, new features include:

New Features

• Dockerfiles and docker images for the 0.1.0 version and for the github main branch. Described in #36
• Covariate correction mode support for controls, whole population, or each clinical group separately. Described in #42
• Toy dataset generation and use capabilities. Described in #32
• More statistical measures added in clinical_groups pipeline. Described #50
• Hyperopt model support, where the model & scaler selection and hyperoptimization is handled automatically by ageml. Described in #47
• A full tutorial and an interactive Colab notebook on how to get started with ageml!

What's Changed

• [ENH] Dockerfiles available for PIP and DEV versions by @itellaetxe in #38
• ENH: Feature toy data by @itellaetxe in #46
• ENH: Feature selective covar correction by @itellaetxe in #47
• ENH: Add hyperopt sklearn support by @itellaetxe in #48
• BUG: Data loading nonfloat bug by @JGarciaCondado in #49
• ENH: Adds more statistics to clinical_groups delta t-tests by @itellaetxe in #51
• CI: Optimize CI jobs by @itellaetxe in #52

0.0.1

Release Notes

First release to present the basic features of AgeML.

Includes:

• Basic functionality: CLI and interactive CLI with options to run age modelling pipeline, correlation analysis of lifestyle factors, age delta comparison between clinical groups, and classification of clinical groups based on modelled age markers.
• Repository minimals: README, LICENSE, Contribution Guide,
  

What's Changed

• [MERGE] Task 4: Build system implementation by @itellaetxe in #1
• [Task 5] Basic Tests (DONE) by @itellaetxe in #2
• Task 1 interactive cli by @JGarciaCondado in #3
• Feature/warnings temp files test by @itellaetxe in #4
• Task 7 clinical groups by @JGarciaCondado in #5
• Task 2 lifestyle factors by @JGarciaCondado in #6
• Task 8 classification by @JGarciaCondado in #7
• Task 3 Separate Genders by @itellaetxe in #8

New Contributors

• @itellaetxe made their first contribution in #1
• @JGarciaCondado made their first contribution in #3

Full Changelog: https://github.com/compneurobilbao/AgeModelling/commits/latest

**AgeML 0.1.0** available, new features include:

• Added systems functionality
• Added covariate correction
• Added more ML models (other than LinearRegressor)
• Encapsulated pipeline commands in separate functions
• Major refactor of ui.py for better encapsulation, readability, and modularity.

What's Changed

• Task 27 encapsulation of pipeline commands by @JGarciaCondado in #13
• [ENH] Add CV parameter setup to Classifier by @JGarciaCondado in #15
• Task 6 multisystems by @itellaetxe in #17
• HOTFIX: [ENH] Added scripts to debug the different CLIs by @itellaetxe in #18
• Task 4 covariate correction by @JGarciaCondado in #19
• Task 10 more ml models by @itellaetxe in #20
• Hotfix whole system classify by @itellaetxe in #22
• Task 17 documentation by @itellaetxe in #23
• Hotfix: change name of factor analysis to factor correlation by @itellaetxe in #24
• Refactoring of Interface command functions structure by @JGarciaCondado in #26

Full Changelog: latest...0.1.0