| Title: |
Effective and Efficient Multilabel Classification in Domains with Large Number of Labels |
| Author(s): |
G. Tsoumakas, I. Katakis, I. Vlahavas.
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| Availability: |
Click here to download the PDF (Acrobat Reader) file (15 pages).
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| Keywords: |
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| Appeared in: |
Proc. ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD'08), Antwerp, Belgium, 2008.
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| Abstract: |
This paper contributes a novel algorithm for effective and computationally efficient multilabel classification in domains with large label sets L. The HOMER algorithm constructs a Hierarchy Of Multilabel classifiERs, each one dealing with a much smaller set of labels compared to L and a more balanced example distribution. This leads to improved predictive performance along with linear training and logarithmic testing complexities with respect to |L|. Label distribution from parent to children nodes is achieved via a new balanced clustering algorithm, called balanced k means. |
| See also : |
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