Ranking Individuals by Group Comparisons
Date Issued
2006
Date
2006
Author(s)
Huang, Tzu-Kuo
DOI
en-US
Abstract
This thesis studies the problem of ranking individuals from their
group competition results. Many real-world problems are of this type. For
example, ranking players
from team games is important in some sports.
In machine learning, this is closely related to
multi-class classification and probability estimates.
Competition results are usually in two types: wins/losses only or wins/losses with scores.
Based on the two types of results,
we propose new models for
estimating individuals' abilities, and hence
rankings of individuals. We
develope easy and effective solution procedures.
Experiments on real bridge records and multi-class
classification demonstrate the viability of the proposed models.
Subjects
排名
團體比較
ranking
group comparisons
Type
thesis
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