An approach based on Decision Tree to agricultural land grading

Abstract

Land resources assessment is the premise and basis for the sustainable utilization of land resources. As a classification technology, Decision Tree has already been applied wildly in the area of information classification. This paper firstly introduces the fundamental theory and characteristics of Decision tree as well as its learning process. Then Iterative Dichotomiser 3 (ID3) algorithm and Decision tree pruning algorithm are combined to construct the Decision tree for agricultural land grading with a good result. The sampling and testing result shows that the accuracy in this case reaches as high as 86%. It can be easily concluded that Decision tree is an effective way for the agriculture land grading.