2006
Franco-Arcega A., Sánchez-Díaz G. y Ruiz-Shulcloper J. ADT: A decision tree algorithm based on concepts. International Symposium on Robotics and Automation ISRA 2006. Vol 2. pp. 35-40, ISBN: 970-769-080-1, 2006
Abstract
In this paper, a new method named Alternative Decision Trees (ADT) for the generation of decision trees is introduced. This proposed method generated a decision tree based in concepts of minimum covering, obtained of concepts or properties of each class described in the data set. Starting from the limitations of others decision tree algorithms, we worked in the development of new techniques that allow us to improve those limitations. A simplification of these concepts, and a split criterion are introduced. Besides, the performance of ADT method is presented.
Multivariate Decision Trees Using Different Splitting Attribute Subsets for Large Datasets
Decision tree induction using a fast splitting attribute selection for large datasets
ADT: A decision tree algorithm based on concepts
A New Incremental Algorithm for Induction of Multivariate Decision Trees for Large Datasets