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» Exploiting multiple classifier types with active learning
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GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 6 months ago
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system
This paper proposes a new smart crossover operator for a Pittsburgh Learning Classifier System. This operator, unlike other recent LCS approaches of smart recombination, does not ...
Jaume Bacardit, Natalio Krasnogor
ICDM
2007
IEEE
162views Data Mining» more  ICDM 2007»
15 years 6 months ago
Exploiting Network Structure for Active Inference in Collective Classification
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
127
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ECML
2004
Springer
15 years 7 months ago
Exploiting Unlabeled Data in Content-Based Image Retrieval
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang
WWW
2008
ACM
16 years 3 months ago
Representing a web page as sets of named entities of multiple types: a model and some preliminary applications
As opposed to representing a document as a "bag of words" in most information retrieval applications, we propose a model of representing a web page as sets of named enti...
Nan Di, Conglei Yao, Mengcheng Duan, Jonathan J. H...
PAA
2002
15 years 2 months ago
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford