Table Evaluator Versions Save

Evaluate real and synthetic datasets against each other

1.6.1

9 months ago

What's Changed

Full Changelog: https://github.com/Baukebrenninkmeijer/table-evaluator/compare/1.6.0...1.6.1

1.6.0

9 months ago

What's Changed

Full Changelog: https://github.com/Baukebrenninkmeijer/table-evaluator/compare/1.5.0...1.6.0

1.5.0

1 year ago

What's Changed

Full Changelog: https://github.com/Baukebrenninkmeijer/table-evaluator/compare/1.4.2...1.5.0

1.4.2

2 years ago
  • Fix seaborn as dependency to 0.11.1 or lower, preventing problematic 0.11.2 which is problematic with this package at the time of writing.

Full Changelog: https://github.com/Baukebrenninkmeijer/table-evaluator/compare/1.4.0...1.4.2

1.4.0

2 years ago

What's Changed

Full Changelog: https://github.com/Baukebrenninkmeijer/table-evaluator/compare/1.3.2...1.4.0

1.3.2

2 years ago

First release in a long time

Includes:

  • Add new release pipeline that uses github actions instead of travis-ci
  • Add requirements file for documentation.
  • Update documentation dependencies, removing m2r and using m2r2

What's Changed

New Contributors

Thanks, guys! 😃

Full Changelog: https://github.com/Baukebrenninkmeijer/table-evaluator/compare/1.3.1...1.3.2

1.2.1

3 years ago
  • Restructured whole project to new modules.
  • Redid documentation with Sphinx rtd theme.
  • Estimator evaluation now also verifies jaccard similarity between predictions of estimators if they are classifiers.

v1.1.5

4 years ago

Fixed integration with dython 0.5.1, which provides cleaner API for associations.

v1.1.4post3

4 years ago

Where is post2 you might ask? Don't ask.

Updating readme to include cooler badges.

v1.1.4post1

4 years ago
  • Updated dython dependency to 0.5.0. Includes tests.
  • Testing associations was changed from comparing two numpy arrays to two dataframes. This includes the index and columns.
  • Tests updates so they can now be run from top-level directory.
  • Improve example notebook
  • Include notebook to generate test data from the sample data.