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**Loza Mencía, Eneldo and Park, Sang-Hyeun and Fürnkranz, Johannes** (2010):

*Efficient Voting Prediction for Pairwise Multilabel Classification.*

73, In: Neurocomputing, (7-9), pp. 1164 - 1176, ISSN 0925-2312, [Online-Edition: http://www.ke.tu-darmstadt.de/publications/papers/neucom10.p...],

[Article]

## Abstract

The pairwise approach to multilabel classification reduces the problem to learning and aggregating preference predictions among the possible labels. A key problem is the need to query a quadratic number of preferences for making a prediction. To solve this problem, we extend the recently proposed QWeighted algorithm for efficient pairwise multiclass voting to the multilabel setting, and evaluate the adapted algorithm on several real-world datasets. We achieve an average-case reduction of classifier evaluations from n^2 to n + n d log n, where n is the total number of possible labels and d is the average number of labels per instance, which is typically quite small in real-world datasets.

Item Type: | Article |
---|---|

Erschienen: | 2010 |

Creators: | Loza Mencía, Eneldo and Park, Sang-Hyeun and Fürnkranz, Johannes |

Title: | Efficient Voting Prediction for Pairwise Multilabel Classification |

Language: | English |

Abstract: | The pairwise approach to multilabel classification reduces the problem to learning and aggregating preference predictions among the possible labels. A key problem is the need to query a quadratic number of preferences for making a prediction. To solve this problem, we extend the recently proposed QWeighted algorithm for efficient pairwise multiclass voting to the multilabel setting, and evaluate the adapted algorithm on several real-world datasets. We achieve an average-case reduction of classifier evaluations from n^2 to n + n d log n, where n is the total number of possible labels and d is the average number of labels per instance, which is typically quite small in real-world datasets. |

Journal or Publication Title: | Neurocomputing |

Volume: | 73 |

Number: | 7-9 |

Uncontrolled Keywords: | efficient classification, learning by pairwise comparison, multilabel classification, voting aggregation |

Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Knowledge Engineering |

Date Deposited: | 24 Jun 2011 14:24 |

Official URL: | http://www.ke.tu-darmstadt.de/publications/papers/neucom10.p... |

Additional Information: | Advances in Computational Intelligence and Learning - 17th European Symposium on Artificial Neural Networks 2009, 17th European Symposium on Artificial Neural Networks 2009 |

Identification Number: | doi:10.1016/j.neucom.2009.11.024 |

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