With the rapid increase of the world’s population, the drastic changes in world’s 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.
['Jun Wu', 'Anastasiya Olesnikova', 'Chi-Hwa Song', 'Won Don Lee']
The Development and Application of Decision Tree for Agriculture Data