An Efficient Approach for Knowledge Discovery in Decision Trees using Inter Quartile Range Transform

Data mining and knowledge discovery is used for discovery of hidden knowledge from large data sources. Decision trees are one of the most famous classification techniques with simple and efficient generalization technique. This paper presents a new decision tree algorithm IQ Tree for classification problem. The IQ Tree assumes using an inter quartile range conversion of attributes with C4.5 as the base algorithm for performing induction can improve all the measures such as accuracy, tree size.