Catfish-sim

Latest version: v0.2.0

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0.2.0

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`.

0.1.0

Overview

0.1.0 is the first version published on PyPI.

Added

- `pyproject.toml` file.

Changed

- Renamed the package to "catfish-sim" for brevity and to align with conventions, as PyPI prefers shorter package names.

Removed

- `Strategy` subclass `AdaptiveWeightedMinimal` and Optuna dependency: This strategy was written to make the agent adapt its reported preferences based on its past success, but the preliminary test results suggested it was not working as intended.

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