A Hierarchical Tree Distance Measure for Classification

Kent Munthe Caspersen, Martin Bjeldbak Madsen, Andreas Berre Eriksen, Bo Thiesson

Abstract

In this paper, we explore the problem of classification where class labels exhibit a hierarchical tree structure. Many multiclass classification algorithms assume a flat label space, where hierarchical structures are ignored. We take advantage of hierarchical structures and the interdependencies between labels. In our setting, labels are structured in a product and service hierarchy, with a focus on spend analysis. We define a novel distance measure between classes in a hierarchical label tree. This measure penalizes paths though high levels in the hierarchy. We use a known classification algorithm that aims to minimize distance between labels, given any symmetric distance measure. The approach is global in that it constructs a single classifier for an entire hierarchy by embedding hierarchical distances into a lower-dimensional space. Results show that combining our novel distance measure with the classifier induces a trade-off between accuracy and lower hierarchical distances on misclassifications. This is useful in a setting where erroneous predictions vastly change the context of a label.

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Paper Citation


in Harvard Style

Munthe Caspersen K., Bjeldbak Madsen M., Berre Eriksen A. and Thiesson B. (2017). A Hierarchical Tree Distance Measure for Classification . In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 502-509. DOI: 10.5220/0006198505020509


in Bibtex Style

@conference{icpram17,
author={Kent Munthe Caspersen and Martin Bjeldbak Madsen and Andreas Berre Eriksen and Bo Thiesson},
title={A Hierarchical Tree Distance Measure for Classification},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={502-509},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006198505020509},
isbn={978-989-758-222-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Hierarchical Tree Distance Measure for Classification
SN - 978-989-758-222-6
AU - Munthe Caspersen K.
AU - Bjeldbak Madsen M.
AU - Berre Eriksen A.
AU - Thiesson B.
PY - 2017
SP - 502
EP - 509
DO - 10.5220/0006198505020509