2010/11/03 by P. Bhargavi, Bhargavi, P., S. Jyothi +1
Agricultural and Biological Sciences · Computer Science · #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Greenhouse Technology and Climate Control #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #cs.NE
paper · pdf · doi:10.48550/arxiv.1011.0800
arxiv created 2010/11/03 · openalex publication_date 2010/11/03 · arxiv updated 2010/11/04 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
This paper details the application of a genetic programming framework for classification of decision tree of Soil data to classify soil texture. The database contains measurements of soil profile data. We have applied GATree for generating classification decision tree. GATree is a decision tree builder that is based on Genetic Algorithms (GAs). The idea behind it is rather simple but powerful. Instead of using statistic metrics that are biased towards specific trees we use a more flexible, global metric of tree quality that try to optimize accuracy and size. GATree offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil texture for soil data set.