International Journal of Soft Computing and Engineering (IJSCE)
In this paper, the short coming of ID3's inclining to choose attributes with many values is discussed, and then a new decision tree algorithm which is improved version of ID3. The authors' proposed methodology uses greedy approach to select the best attribute. To do so the information gain is used. The attribute with highest information gain is selected. If information gain is not good then again divide attributes values into groups. These steps are done until they get good classification/misclassification ratio. The proposed algorithms classify the data sets more accurately and efficiently.