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Learning classifier system

Known as: Classifier system, LCS 
Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a… 
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Related topics

Related topics

38 relations
Artificial immune systemArtificial intelligenceArtificial neural networkAssociation rule learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2015
Highly Cited
2015
An improved early detection method of type-2 diabetes mellitus using multiple classifier system
Highly Cited
2014
Highly Cited
2014
A novel approach for change detection of remotely sensed images using semi-supervised multiple classifier system
2013
2013
Performance comparison of feature vector extraction techniques in RGB color space using block truncation coding for content based image classification with discrete classifiers
Content based image classification is a vital component of machine learning and is attaining increasing importance in the field… 
Highly Cited
2008
Highly Cited
2008
Prototype reduction using an artificial immune model
Artificial immune system (AIS)-based pattern classification approach is relatively new in the field of pattern recognition. The… 
Highly Cited
2007
Highly Cited
2007
Instace-Based AMN Classification for Improved Object Recognition in 2D and 3D Laser Range Data
In this paper, we present an algorithm to identify different types of objects from 2D and 3D laser range data. Our method is a… 
2006
2006
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter… 
Highly Cited
1999
Highly Cited
1999
Automatic diagnosis with genetic algorithms and case-based reasoning
Highly Cited
1997
Highly Cited
1997
Discovering Risk of Disease with a Learning Classifier System
A learning classifier system, EpiCS, was used to de rive a continuous measure of disease risk in a series of 250 individuals… 
Highly Cited
1994
Highly Cited
1994
A New Approach to Genetic Based Machine Learning and an Efficient Finding of Fuzzy Rules - Proposal of Nagoya Approach -
This paper presents a new approach to genetic-based machine learning (GBML). The new approach utilizes mechanisms of genetic… 
Highly Cited
1989
Highly Cited
1989
Recognizing Hand-Printed Letters and Digits
We are developing a hand-printed character recognition system using a multi-layered neural net trained through backpropagation… 
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