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IDEAL
2000
Springer
15 years 1 months ago
Observational Learning with Modular Networks
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for ...
Hyunjung Shin, Hyoungjoo Lee, Sungzoon Cho
IDEAL
2009
Springer
15 years 4 months ago
Clustering with XCS and Agglomerative Rule Merging
Abstract. In this paper, we present a more effective approach to clustering with eXtended Classifier System (XCS) which is divided into two phases. The first phase is the XCS le...
Liangdong Shi, Yinghuan Shi, Yang Gao
ECAI
2000
Springer
15 years 2 months ago
Designing Clustering Methods for Ontology Building - The Mo'K Workbench
This paper describes Mo’K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo’K is intended to assist ontology de...
Gilles Bisson, Claire Nedellec, Dolores Cañ...
CIBCB
2006
IEEE
15 years 4 months ago
Visualization of Support Vector Machines with Unsupervised Learning
– The visualization of support vector machines in realistic settings is a difficult problem due to the high dimensionality of the typical datasets involved. However, such visuali...
Lutz Hamel
IDA
2003
Springer
15 years 3 months ago
A Semi-supervised Method for Learning the Structure of Robot Environment Interactions
For a mobile robot to act autonomously, it must be able to construct a model of its interaction with the environment. Oates et al. developed an unsupervised learning method that pr...
Axel Großmann, Matthias Wendt, Jeremy Wyatt