CSDTM A Cost Sensitive Decision Tree Based Method

Making a decision has often many results and repercussions. These results don’t have the same importance according to the considered phenomenon. This situation can be described by the introduction of the cost concept in the learning process. In this article, we propose a method able to integrate the costs in the automatic learning process. We focus our work on the misclassification cost and we use decision trees as a supervised learning technique. Promising results are obtained using the proposed method.