Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices
Abstract
In many machine learning problems, the performance of the results is measured by indices that often combine precision and recall. In this paper, we study the behavior of such indices in function of the tradeoff precision-recall. We present a new tool of performance visualization and analysis referred to the tradeoff space, which plots the performance index in function of the precision-recall tradeoff. We analyse the properties of this new space and show its advantages over the precision-recall space. Code related to this paper is available at: https://sites.google.com/site/bhanczarhomepage/prerec .
Cite
Text
Hanczar and Nadif. "Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2018. doi:10.1007/978-3-030-10925-7_42Markdown
[Hanczar and Nadif. "Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2018.](https://mlanthology.org/ecmlpkdd/2018/hanczar2018ecmlpkdd-controlling/) doi:10.1007/978-3-030-10925-7_42BibTeX
@inproceedings{hanczar2018ecmlpkdd-controlling,
title = {{Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices}},
author = {Hanczar, Blaise and Nadif, Mohamed},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2018},
pages = {687-702},
doi = {10.1007/978-3-030-10925-7_42},
url = {https://mlanthology.org/ecmlpkdd/2018/hanczar2018ecmlpkdd-controlling/}
}