A decision tree model for mineral potential mapping
基于决策树的矿产资源潜力制图模型

A new Decision Tree model for mineral resource potential mapping is proposed. In order to apply this new model, three-step procedure was needed as followed: the first step is to get training samples from study area ; the second step is to abstract the structure of spacial information of training samples and then to construct Decision Tree; the last step is to generate the distributive map of mineral resource potentials. In this paper, the model has been applied to predict multi-metallogenetic prospecting targets in the district from Duolanasayi to Ashele in northern XinJiang. The predicted targets by the model are compared with the C-F model. The two model results are very similar to each other, this prove that the new model is effective and practical.