Title :
The Development and Application of Decision Tree for Agriculture Data
Author :
Wu, Jun ; Olesnikova, Anastasiya ; Song, Chi-Hwa ; Lee, Won Don
Author_Institution :
Dept. of Comput. Sci., Chungnam Nat. Univ.
Abstract :
With the rapid increase of the worldpsilas population, the drastic changes in worldpsilas food supply, and the limitation of land resources, the pressure for agriculture is greater than ever before. With the development of AI theories and technologies, the study in the classification of agriculture data becomes more advanced and intellectualized. This paper mainly discusses a specific decision tree classifier which is used to predict and classify agriculture data. It is capable of dealing with both complete data and incomplete data. So that it can be applied into the classification problem for all kinds of agriculture data sets. The experiments are designed to prove the advantage of the proposed algorithm.
Keywords :
agricultural engineering; decision trees; learning (artificial intelligence); pattern classification; AI theory; agriculture data classification; decision tree classifier application; land resource limitation; machine learning; world food supply; Agriculture; Algorithm design and analysis; Decision trees; Design optimization; Economic forecasting; Fluctuations; Genetic algorithms; Genetic mutations; Neural networks; Sugar industry; Agriculture Data; Decision Tree;
Conference_Titel :
Intelligent Information Technology and Security Informatics, 2009. IITSI '09. Second International Symposium on
Conference_Location :
Moscow
Print_ISBN :
978-1-4244-3580-7
DOI :
10.1109/IITSI.2009.10
