v0.2.0

Added

• DictBasedPreference: A new preference class that can be used to exactly specify the compatibility score for all attribute values. While CategoricalPreference class was able to handle value-compatibility dictionaries, DictBasedPreference allows setting a default compatibility score for attribute values that are not specified, and its parameters are more intuitive to use with a dictionary.
• A "getting started" tutorial in the documentation.
• Missing parameter explanations in the docstrings.
• LLCP2022 dataset ranges for age, height, and BMI for ease of use.

Changed

• Added deal-breaker consideration for RankedAgentMatcher: It is now possible to consider one-sided or two-sided deal-breakers while making recommendations.
• Other minor code and documentation improvements, typo fixes.

Developer notes

• scikit-learn was intended to be dropped from the dependencies. However, due to self-written min-max scaling functions not yielding the exact same results with the one imported from scikit-learn, it was decided to keep scikit-learn.
• CategoricalPreference still has the functionality to handle compatibility dictionaries, but this feature may be deprecated in later versions, as there is now a specific class for dictionaries, DictBasedPreference.

v0.1.1

Changes:

• Documentation-related fixes.