Appavu Alias Balamurugan Subramanian, S. Pramala, B. Rajalakshmi and Ramasamy Rajaram. Improving Decision Tree Performance by Exception Handling. International Journal of Automation and Computing, vol. 7, no. 3, pp. 372-380, 2010. DOI: 10.1007/s11633-010-0517-5
Citation: Appavu Alias Balamurugan Subramanian, S. Pramala, B. Rajalakshmi and Ramasamy Rajaram. Improving Decision Tree Performance by Exception Handling. International Journal of Automation and Computing, vol. 7, no. 3, pp. 372-380, 2010. DOI: 10.1007/s11633-010-0517-5

Improving Decision Tree Performance by Exception Handling

  • This paper focuses on improving decision tree induction algorithms when a kind of tie appears during the rule generation procedure for specific training datasets. The tie occurs when there are equal proportions of the target class outcome in the leaf node s records that leads to a situation where majority voting cannot be applied. To solve the above mentioned exception, we propose to base the prediction of the result on the naive Bayes (NB) estimate, k-nearest neighbour (k-NN) and association rule mining (ARM). The other features used for splitting the parent nodes are also taken into consideration.
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