Algorithm for Generating Decision Tree Based on Incomplete Information Systems

Decision trees are a kind of effective data mining methods to case classification.During processing objects with missing values in the incomplete information systems,the guessing technologies are often used in most of the existing decision tree algorithms.In this paper,we defined a condition attribute's decision support degree with respect to the decision attribute with the concept of a maximal consistent block,which can be regarded as the heuristic information.Moreover,we proposed an algorithm for generating a decision tree from an incomplete information system,which called IDTBDS.Note that the proposed algorithm not only fast extract the rule sets,and but also these rules possess more classification accuracy.