An Improved Algorithm of Decision Tree ID3 Algorithm

First,ID3 algorithm's basic principles and major shortcomings have been analyzed simply,and then for the main shortcoming of ID3 algorithm that tends to select a attribute which has many values in the course of selecting split-properties,and then the ID3 algorithm has been improved by introducing a correction function and Proposing a hypothesis of independence.Theoretical analysis and experimen tal results show that the improved algorithm,to some extent,not only better compensate for the lack of multi-valued bias of the largest,but also greatly simplifies the algorithm process,improve the classification accuracy significantly and accelerate the speed of decision tree construction.