Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.5121/ijcsit.2010.2514 | International Journal of Computer Science and Information Technology |
Keywords | Field | DocType |
soil texture,soil profile,data mining,evolutionary computing,genetic algorithm,classification,soil classification,decision tree | Data mining,Decision tree,Computer science,Genetic programming,Artificial intelligence,ID3 algorithm,Soil texture,Soil classification,Machine learning,Decision tree learning,Genetic algorithm,Incremental decision tree | Journal |
Volume | Issue | Citations |
abs/1011.0 | 5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Bhargavi | 1 | 0 | 0.68 |
| S. Jyothi | 2 | 0 | 0.68 |