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ICTAI
2008
IEEE
14 years 1 months ago
Ensemble Learning of Regional Classifiers
We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and ...
Byungwoo Lee, Yong-chan Na, Byonghwa Oh, Jihoon Ya...
VLSISP
2010
254views more  VLSISP 2010»
13 years 5 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
ECML
1998
Springer
13 years 11 months ago
Learning to Classify X-Ray Images Using Relational Learning
: Image understanding often requires extensive background knowledge. The problem addressed in this paper is such knowledge can be acquired. We discuss how relational machine learni...
Claude Sammut, Tatjana Zrimec
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 7 months ago
Adapted Pittsburgh classifier system: building accurate strategies in non markovian environments
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments con...
Gilles Énée, Mathias Péroumal...
AAAI
1996
13 years 8 months ago
A Graph-Based Method for Improving GSAT
GSAT is a randomized greedy local repair procedure that was introduced for solving propositional satis ability and constraint satisfaction problems. We present an improvement to G...
Kalev Kask, Rina Dechter