The Area under the ROC Curve as a Criterion for Clustering Evaluation

Helena Aidos, Robert P. W. Duin, Ana Fred

2013

Abstract

In the literature, there are several criteria for validation of a clustering partition. Those criteria can be external or internal, depending on whether we use prior information about the true class labels or only the data itself. All these criteria assume a fixed number of clusters k and measure the performance of a clustering algorithm for that k. Instead, we propose a measure that provides the robustness of an algorithm for several values of k, which constructs a ROC curve and measures the area under that curve. We present ROC curves of a few clustering algorithms for several synthetic and real-world datasets and show which clustering algorithms are less sensitive to the choice of the number of clusters, k. We also show that this measure can be used as a validation criterion in a semi-supervised context, and empirical evidence shows that we do not need always all the objects labeled to validate the clustering partition.

Paper Citation

in Harvard Style

Aidos H., P. W. Duin R. and Fred A. (2013). The Area under the ROC Curve as a Criterion for Clustering Evaluation . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 276-280. DOI: 10.5220/0004265502760280

in Bibtex Style

@conference{icpram13,
author={Helena Aidos and Robert P. W. Duin and Ana Fred},
title={The Area under the ROC Curve as a Criterion for Clustering Evaluation},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={276-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004265502760280},
isbn={978-989-8565-41-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - The Area under the ROC Curve as a Criterion for Clustering Evaluation
SN - 978-989-8565-41-9
AU - Aidos H.
AU - P. W. Duin R.
AU - Fred A.
PY - 2013
SP - 276
EP - 280
DO - 10.5220/0004265502760280