Title :
An improved decision tree algorithm and its application in maize seed breeding
Author :
Ji Dan ; Qiu Jianlin ; Chen Jianping ; Chen Li ; He Peng
Author_Institution :
Dept. of Comput. Sci. & Technol., Nantong Univ., Nantong, China
Abstract :
The application of information technology in agriculture accelerates the digitization of agriculture information. How to analyze mass of agriculture data and reveal inherent knowledge are becoming new research points. Effective application of data mining technology can achieve this purpose. This paper presents a new improved CA algorithm based on traditional decision tree method. It introduces a pretreatment theory about double dimension reduction which can deal with large and high-scale datasets. By using CA algorithm in maize seed breeding, we can analyze the potential rules and find useful information from it to direct the growth of maize. The experiments show the improved CA algorithm can obtain more intuitive and efficient information.
Keywords :
agriculture; crops; data mining; decision trees; CA algorithm; agriculture data; data mining technology; dimension reduction; improved decision tree algorithm; maize seed breeding; Algorithm design and analysis; Classification algorithms; Classification tree analysis; Clustering algorithms; Ear; Partitioning algorithms; Decision Tree; Dimension Reduction; Maize Seed Breeding;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583344
