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» Results of the KDD'99 Classifier Learning
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CEC
2005
IEEE
13 years 9 months ago
On the use of rule-sharing in learning classifier system ensembles
This paper presents an investigation into exploiting the population-based nature of Learning Classifier Systems for their use within highly-parallel systems. In particular, the use...
Larry Bull, Matthew Studley, Anthony J. Bagnall, I...
BMCBI
2010
140views more  BMCBI 2010»
13 years 5 months ago
An improved machine learning protocol for the identification of correct Sequest search results
Background: Mass spectrometry has become a standard method by which the proteomic profile of cell or tissue samples is characterized. To fully take advantage of tandem mass spectr...
Morten Kallberg, Hui Lu
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 7 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
13 years 11 months ago
Classifier systems that compute action mappings
The learning in a niche based learning classifier system depends both on the complexity of the problem space and on the number of available actions. In this paper, we introduce a ...
Pier Luca Lanzi, Daniele Loiacono
ICONIP
2010
13 years 5 months ago
Exploring Features and Classifiers to Classify MicroRNA Expression Profiles of Human Cancer
Recently, some non-coding small RNAs, known as microRNAs (miRNA), have drawn a lot of attention to identify their role in gene regulation and various biological processes. The miRN...
Kyung-Joong Kim, Sung-Bae Cho