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» Evaluating learning algorithms and classifiers
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CVPR
1998
IEEE
14 years 11 months ago
An Optimized Interaction Strategy for Bayesian Relevance Feedback
A new algorithm and systematic evaluation is presented for searching a database via relevance feedback. It represents a new image display strategy for the PicHunter system [2, 1]....
Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka...
WWW
2004
ACM
14 years 9 months ago
OntoMiner: bootstrapping ontologies from overlapping domain specific web sites
In this paper, we present automated techniques for bootstrapping and populating specialized domain ontologies by organizing and mining a set of relevant overlapping Web sites prov...
Hasan Davulcu, Srinivas Vadrevu, Saravanakumar Nag...
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
14 years 2 months ago
Evolutionary change in developmental timing
This paper presents a mutation-based evolutionary algorithm that evolves genotypic genes for regulating developmental timing of phenotypic values. The genotype sequentially genera...
Kei Ohnishi, Kaori Yoshida
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
14 years 2 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...
AAAI
2006
13 years 10 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch