ABSRACT: A Holland learning classifier system is one of the methods for applying a genetic-based approach to machine learning applications. An enhanced version of the system that employs the Bucket-brigade algorithm to reward individuals in a chain of co-operating rules is implemented and assigned the task of learning rules for classifying simple objects. Results are presented which show that the system was able to learn rules for the task. It is argued that a classifier based learning method requires little training examples and that by its use of genetic algorithms to search for new plausible rules, the method should be able to cope with changing conditions. However, the results appear to indicate that the use of bucket-brigade as a fitne...
In the intersection of pattern recognition, machine learning, and evolutionary computation is a new ...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46947/1/10994_2005_Article_422926.pd
Classifier systems are rule-based adaptive systems whose learning capabilities emerge from processes...
Classifier systems are massively parallel, message-passing, rule-based systems that learn through cr...
Rules are an accepted means of representing knowledge for virtually every domain. Traditional machin...
This book provides a unified framework that describes how genetic learning can be used to design pat...
Abstract—The classification problem can be addressed by numerous techniques and algorithms which bel...
This paper examines the possibility of using evolutionary learning methods for classification. Great...
Classification rule mining from huge amount of data is a challenging issue in data mining. Classific...
Congress on Evolutionary Computation. Washington, DC, 6-9 July 1999.One of the major problems relate...
Classifier systems are currently in vogue as a way of using genetic algorithms to demonstrate machin...
Abstract—Classification is one of the most researched questions in machine learning and data mining....
Classification is the supervised learning technique of data mining which is used to extract hidden u...
Genetic algorithms are one of the most commonly used approaches in data mining. In this article, we ...
Genetic Algorithm is a widely used approach in predictive data mining where data mining output can b...
In the intersection of pattern recognition, machine learning, and evolutionary computation is a new ...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46947/1/10994_2005_Article_422926.pd
Classifier systems are rule-based adaptive systems whose learning capabilities emerge from processes...
Classifier systems are massively parallel, message-passing, rule-based systems that learn through cr...
Rules are an accepted means of representing knowledge for virtually every domain. Traditional machin...
This book provides a unified framework that describes how genetic learning can be used to design pat...
Abstract—The classification problem can be addressed by numerous techniques and algorithms which bel...
This paper examines the possibility of using evolutionary learning methods for classification. Great...
Classification rule mining from huge amount of data is a challenging issue in data mining. Classific...
Congress on Evolutionary Computation. Washington, DC, 6-9 July 1999.One of the major problems relate...
Classifier systems are currently in vogue as a way of using genetic algorithms to demonstrate machin...
Abstract—Classification is one of the most researched questions in machine learning and data mining....
Classification is the supervised learning technique of data mining which is used to extract hidden u...
Genetic algorithms are one of the most commonly used approaches in data mining. In this article, we ...
Genetic Algorithm is a widely used approach in predictive data mining where data mining output can b...
In the intersection of pattern recognition, machine learning, and evolutionary computation is a new ...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46947/1/10994_2005_Article_422926.pd
Classifier systems are rule-based adaptive systems whose learning capabilities emerge from processes...