Metadata-Version: 2.4
Name: fractional-information-gain
Version: 1.0.0
Summary: Library for computing Fractional Information Gain metrics.
Author: Thomas Christie, Markus Hauru, Anna Rafferty
License-Expression: MIT
Project-URL: Homepage, https://github.com/RenaissancePhilanthropy/fractional-information-gain
Project-URL: Documentation, https://renaissancephilanthropy.github.io/fractional-information-gain/
Project-URL: Repository, https://github.com/RenaissancePhilanthropy/fractional-information-gain
Project-URL: Issues, https://github.com/RenaissancePhilanthropy/fractional-information-gain/issues
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Typing :: Typed
Requires-Python: <3.15,>=3.12
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy~=2.4
Provides-Extra: torch
Requires-Dist: torch~=2.10; extra == "torch"
Dynamic: license-file

# fractional-information-gain

**Fractional Information Gain (FIG)** is a performance metric for knowledge-tracing
models in educational assessment, available in Python (NumPy and PyTorch) and R.

**Documentation (installation, usage, and API):
https://renaissancephilanthropy.github.io/fractional-information-gain/**

## Contributing

Development and release instructions are in
[CONTRIBUTING.md](https://github.com/RenaissancePhilanthropy/fractional-information-gain/blob/main/CONTRIBUTING.md).
