Classification knowledge discovery in mold tooling test using decision tree algorithm
Journal of Intelligent Manufacturing
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Aiming at the insufficiencies of traditional agricultural land grading methods, this study discussed the process and technical route of agricultural land grading based on decision tree analysis method and GIS, constructed an agricultural land grading model based on MATLAB and decision tree C4.5 algorithm. Furthermore, We took Luanwan village of Pingyin county in China for the empirical study, selected seven indicators as the test attributes, predicted agricultural land grade on support of this model, and expressed the rules in the quantitative way. The results showed that agricultural land grading model based on decision tree which is coded in M-language of MATLAB doesn’t rely on the empirical knowledge. It has the ability of self-learning, and the gained rules are easy to be understood. Moreover, the high rate of accuracy will be able to meet the requirements of evaluation.