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Evalica, your favourite evaluation toolkit

Evalica

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Evalica is a Python library that transforms pairwise comparisons into ranked lists of items. It offers convenient high-performant Rust implementations of the corresponding methods via PyO3, and additionally provides naïve Python code for most of them. Evalica is fully compatible with NumPy arrays and pandas data frames.

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Installation

  • pip: pip install evalica
  • Anaconda: conda install conda-forge::evalica

Usage

Imagine that we would like to rank the different meals and have the following dataset of three comparisons produced by food experts.

Item X Item Y Winner
pizza burger x
burger sushi y
pizza sushi tie

Given this hypothetical example, Evalica takes these three columns and computes the outcome of the given pairwise comparison according to the chosen model. Note that the first argument is the column Item X, the second argument is the column Item Y, and the third argument corresponds to the column Winner.

>>> from evalica import elo, Winner
>>> result = elo(
...     ['pizza', 'burger', 'pizza'],
...     ['burger', 'sushi', 'sushi'],
...     [Winner.X, Winner.Y, Winner.Draw],
... )
>>> result.scores
pizza     1014.972058
burger     970.647200
sushi     1014.380742
Name: elo, dtype: float64

As a result, we obtain Elo scores of our items. In this example, pizza was the most favoured item, sushi was the runner-up, and burger was the least preferred item.

Item Score
pizza 1014.97
burger 970.65
sushi 1014.38

Command-Line Interface

Evalica also provides a simple command-line interface, allowing the use of these methods in shell scripts and for prototyping.

$ evalica -i food.csv bradley-terry
item,score,rank
Tacos,0.43428827947351706,1
Sushi,0.19060105855071743,2
Burger,0.14797720376982199,3
Pasta,0.12815347866987045,4
Pizza,0.0989799795360731,5

Refer to the food.csv file as an input example.

Implemented Methods

Method In Python In Rust
Counting
Average Win Rate
Bradley–Terry
Elo
Eigenvalue
PageRank
Newman

Copyright

Copyright (c) 2024 Dmitry Ustalov. See LICENSE for details.