DMCA
Multi-label classification on tree- and DAG-structured hierarchies (2011)
| Venue: | In ICML |
| Citations: | 24 - 2 self |
BibTeX
@INPROCEEDINGS{Bi11multi-labelclassification,
author = {Wei Bi and James T. Kwok},
title = {Multi-label classification on tree- and DAG-structured hierarchies},
booktitle = {In ICML},
year = {2011}
}
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Abstract
Many real-world applications involve multilabel classification, in which the labels are organized in the form of a tree or directed acyclic graph (DAG). However, current research efforts typically ignore the label dependencies or can only exploit the dependencies in tree-structured hierarchies. In this paper, we present a novel hierarchical multilabel classification algorithm which can be used on both tree- and DAG-structured hierarchies. The key idea is to formulate the search for the optimal consistent multi-label as the finding of the best subgraph in a tree/DAG. Using a simple greedy strategy, the proposed algorithm is computationally efficient, easy to implement, does not suffer from the problem of insufficient/skewed training data in classifier training, and can be readily used on large hierarchies. Theoretical results guarantee the optimality of the obtained solution. Experiments are performed on a large number of functional genomics data sets. The proposed method consistently outperforms the state-of-the-art method on both tree- and DAG-structured hierarchies. 1.
Keyphrases
dag-structured hierarchy multi-label classification tree dag multilabel classification novel hierarchical multilabel classification classifier training acyclic graph key idea simple greedy strategy tree-structured hierarchy state-of-the-art method large number label dependency optimal consistent multi-label theoretical result functional genomics data set large hierarchy obtained solution many real-world application current research effort
