Predicting the Value of a Target Attribute Using Data Mining
Ravijeet Singh Chauhan
Ravijeet Singh Chauhan, Computer Science Department, Samrat Ashok Technological Institute, Vidisha, Madhya Pradesh, India.
Manuscript received on April 06, 2013. | Revised Manuscript received on April 28, 2013. | Manuscript published on May 05, 2013. | PP: 309-311 | Volume-3, Issue-2, May 2013. | Retrieval Number: B1554053213/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Classification, Decision tree, ID3, Prediction, Clustering.