AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS

Omar Ali, Giovanni Zappella, Tijl De Bie, Nello Cristianini

2012

Abstract

The task of predicting the label of a network node, based on the labels of the remaining nodes, is an area of growing interest in machine learning, as various types of data are naturally represented as nodes in a graph. As an increasing number of methods and approaches are proposed to solve this task, the problem of comparing their performance becomes of key importance. In this paper we present an extensive experimental comparison of 15 different methods, on 15 different labelled-networks, as well as releasing all datasets and source code. In addition, we release a further set of networks that were not used in this study (as not all benchmarked methods could manage very large datasets). Besides the release of data, protocols and algorithms, the key contribution of this study is that in each of the 225 combinations we tested, the best performance—both in accuracy and running time—was achieved by the same algorithm: Online Majority Vote. This is also one of the simplest methods to implement.

Paper Citation

in Harvard Style

Ali O., Zappella G., De Bie T. and Cristianini N. (2012). AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-8425-99-7, pages 259-268. DOI: 10.5220/0003695702590268

in Bibtex Style

@conference{icpram12,
author={Omar Ali and Giovanni Zappella and Tijl De Bie and Nello Cristianini},
title={AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2012},
pages={259-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003695702590268},
isbn={978-989-8425-99-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS
SN - 978-989-8425-99-7
AU - Ali O.
AU - Zappella G.
AU - De Bie T.
AU - Cristianini N.
PY - 2012
SP - 259
EP - 268
DO - 10.5220/0003695702590268