A Novel Approach to Design Classifier Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{muni:2004:TEC,

• author = "Durga Prasad Muni and Nikhil R Pal and Jyotirmay Das",
• title = "A Novel Approach to Design Classifier Using Genetic Programming",
• journal = "IEEE Transactions on Evolutionary Computation",
• year = "2004",
• volume = "8",
• number = "2",
• pages = "183--196",
• month = apr,
• email = "muni_r@isical.ac.in, nikhi@isical.ac.in, jdas@isical.ac.in",
• keywords = "genetic algorithms, genetic programming, classification, multi-tree concept",
• URL = "http://www.isical.ac.in/~muni_r",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.7129",
• DOI = "doi:10.1109/TEVC.2004.825567",
• size = "14 pages",
• abstract = "We propose a new approach for designing classifiers for a c-class c>=2 problem using Genetic Programming (GP). The proposed approach takes an integrated view of all classes when the GP evolves. A multi-tree representation of chromosomes is used. In this context, we propose a modified crossover operation and a new mutation operation that reduces the destructive nature of conventional genetic operations. A new concept of unfitness of a tree is used to select trees for genetic operations. This gives more opportunity for unfit trees to become fit. A new concept of OR-ing chromosomes in the terminal population is introduced, which enables us to get a classifier with better performance. Finally, a weight based scheme and a heuristic rule based scheme characterising typical mistakes are used for conflict resolution. The classifier is capable of saying ``don't know'' when faced with unfamiliar examples. The effectiveness of our scheme is demonstrated on several real data sets.",
• notes = "UCI machine learning benchmarks",

}

Genetic Programming entries for Durga Prasad Muni Nikhil Ranjan Pal Jyotirmay Das

Citations