A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains
Abstract
Classifier performance evaluation typically gives rise to a multitude of results that are difficult to interpret. On the one hand, a variety of different performance metrics can be applied, each adding a little bit more information about the classifiers than the others; and on the other hand, evaluation must be conducted on multiple domains to get a clear view of the classifier’s general behaviour.
Cite
Text
Alaíz-Rodríguez et al. "A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2008. doi:10.1007/978-3-540-87481-2_43Markdown
[Alaíz-Rodríguez et al. "A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2008.](https://mlanthology.org/ecmlpkdd/2008/alaizrodriguez2008ecmlpkdd-visualizationbased/) doi:10.1007/978-3-540-87481-2_43BibTeX
@inproceedings{alaizrodriguez2008ecmlpkdd-visualizationbased,
title = {{A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains}},
author = {Alaíz-Rodríguez, Rocío and Japkowicz, Nathalie and Tischer, Peter E.},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2008},
pages = {660-665},
doi = {10.1007/978-3-540-87481-2_43},
url = {https://mlanthology.org/ecmlpkdd/2008/alaizrodriguez2008ecmlpkdd-visualizationbased/}
}