A Survey on the Application of Genetic Programming to Classification
University of Córdoba · Universidad de Granada
Abstract
Classification is one of the most researched questions in machine learning and data mining. A wide range of real problems have been stated as classification problems, for example credit scoring, bankruptcy prediction, medical diagnosis, pattern recognition, text categorization, software quality assessment, and many more. The use of evolutionary algorithms for training classifiers has been studied in the past few decades. Genetic programming (GP) is a flexible and powerful evolutionary technique with some features that can be very valuable and suitable for the evolution of classifiers. This paper surveys existing literature about the application of genetic programming to classification, to show the different…
Citation impact
- FWCI
- 37.13
- Percentile
- 100%
- References
- 209
Authors
3Topics & keywords
- Genetic programming
- Computer science
- Machine learning
- Categorization
- Artificial intelligence
- Evolutionary algorithm
- Genetic algorithm
- Quality (philosophy)