50 search results - page 1 / 10 » A Selective Sampling Strategy for Label Ranking |
ECML
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
KDD
2005
ACM
14 years 5 months ago
2005
ACM
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
IIR
2010
13 years 6 months ago
2010
Given a classifier trained on relatively few training examples, active learning (AL) consists in ranking a set of unlabeled examples in terms of how informative they would be, if ...
ICPR
2004
IEEE
14 years 6 months ago
2004
IEEE
In this paper, a new selective sampling method for the active learning framework is presented. Initially, a small training set ? and a large unlabeled set ? are given. The goal is...
KDD
2009
ACM
14 years 5 months ago
2009
ACM
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...