MobileTeleSystems Ambrosia Versions Save

Hotfix for pyspark import in spark criteria.

• Documentation and usage examples have been substantially reworked and updated.

• The Designer class and design methods functionality is updated.

  • Empirical design now supports the choice of hypothesis alternative and group ratio parameter

  • Look of resulting tables with calculated parameters is unified for all design methods

  • Changed multiprocessing strategy for bootstrap criterion

• The Tester class functionality is updated.

  • Spark data support for the Tester class is added. Independent t-test is available now

  • Bootstrap criterion can now return deterministic output using a random_seed parameter

  • Paired bootstrap criterion is now available

  • MHC now is optional and takes into account the number of passed metrics

  • first_errors parameter renamed to first_type_errors

• pyspark package now is optional and could be installed using pip extras.

• Fixed a set of bugs.

In these release we introduce the following updates:

• The Designer theoretical methods now can be used for the binary data
• The Designer theoretical methods now supports hypothesis alternative and group ratio parameters
• All individual data processing classes have been updated to use the fit and transform methods
• IQRPreprocessor, BoxCoxTransformer, LogTransformer classes have been added in ambrosia.preprocessing
• The Preprocessor class now can store all transformation in one json file
• The MLVarianceReducer can store and load picklable ML model
• Other changes in data processing classes

You can see the detailed changelog here: https://github.com/MobileTeleSystems/Ambrosia/blob/main/CHANGELOG.rst

Library name changed back to ambrosia. Naming conflict in PyPI has been resolved.
0.1.x versions are still available in PyPI under ambrozia name.

T-test absolute effect calculation bug fix.

Hotfix for library naming. Library temporary renamed to ambrozia in PyPI repository due to hidden naming conflict.

First release

First release of Ambrosia package:

• Added Designer class for experiment parameters design
• Added Spliiter class for A/B groups split
• Added Tester class for experiment effect measurement
• Added various classes for experiment data preprocessing
• Added A/B testing tools with wide functionality