Predicting the Value of a Target Attribute Using Data Mining

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. Our 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 we get good classification/misclassification ratio. The proposed algorithms classify the data sets more accurately and efficiently.

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