This paper presents ranx, a Python evaluation library for Information Retrieval built on top of Numba. ranx provides a user-friendly interface to the most common ranking evaluation metrics, such as MAP, MRR, and NDCG. Moreover, it offers a convenient way of managing the evaluation results, comparing different runs, performing statistical tests between them, and exporting LaTeX tables ready to be used in scientific publications, all in a few lines of code. The efficiency brought by Numba, a just-in-time compiler for Python code, makes the adoption ranx convenient even for industrial applications.
Bassani, E. (2022). ranx: A Blazing-Fast Python Library for Ranking Evaluation and Comparison. In Advances in Information Retrieval. ECIR 2022 (pp.259-264). GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-99739-7_30].
ranx: A Blazing-Fast Python Library for Ranking Evaluation and Comparison
Bassani E.
Primo
2022
Abstract
This paper presents ranx, a Python evaluation library for Information Retrieval built on top of Numba. ranx provides a user-friendly interface to the most common ranking evaluation metrics, such as MAP, MRR, and NDCG. Moreover, it offers a convenient way of managing the evaluation results, comparing different runs, performing statistical tests between them, and exporting LaTeX tables ready to be used in scientific publications, all in a few lines of code. The efficiency brought by Numba, a just-in-time compiler for Python code, makes the adoption ranx convenient even for industrial applications.
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