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ICML
2008
IEEE

Multiple instance ranking

15 years 10 days ago
Multiple instance ranking
This paper introduces a novel machine learning model called multiple instance ranking (MIRank) that enables ranking to be performed in a multiple instance learning setting. The motivation for MIRank stems hydrogen abstraction problem in computational chemistry, that of predicting the group of hydrogen atoms from which en is abstracted (removed) during metabolism. The model predicts the preferred hydrogen group within a molecule by ranking the groups, with the ambiguity of not knowing which hydrogen atom within the d group is actually abstracted. This paper formulates MIRank in its general context and proposes an algorithm for solving MIRank problems using successive linear programming. The method outperforms multiple instance classification models on several real and synthetic datasets.
Charles Bergeron, Jed Zaretzki, Curt M. Breneman,
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2008
Where ICML
Authors Charles Bergeron, Jed Zaretzki, Curt M. Breneman, Kristin P. Bennett
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