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논문검색

A Novel Decision Tree Framework using Discrete Haar Wavelet Transform

초록

영어

Data Mining is a popular knowledge discovery technique. In data mining decision trees are of the simple and powerful decision making models. One of the limitations in decision trees is towards the data source which they tackle. If data sources which are given as input to decision tree are of imbalance nature then the efficiency of decision tree drops drastically, we propose a decision tree structure which uses discrete haar wavelet transformation technique along with a filter. In this paper, we propose a novel method WT Tree based on above strategy. Extensive experiments, using C4.5 decision tree as base classifier, show that the performance measures of our method is comparable to state-of-the-art methods.

목차

Abstract
 1. Introduction
 2. Recent Advances in Decision Trees
 3. Proposed Method
  3.1. Wavelet Transform
  3.2. Wavelet Transform Decision Tree Framework
 4. Experimental Design and Evaluation Criteria's
 5. Results
 6. Conclusion
 References

저자정보

  • Bhanu Prakash Battula Department of Computer Science and Engineering, Vignan’sNirula Institute of Technology and Science, Guntur, Andhra Pradesh, India
  • KVSS Rama Krishna Department of Computer Science and Engineering, Vignan’sNirula Institute of Technology and Science, Guntur, Andhra Pradesh, India
  • Debnath Bhattacharyya Department of Information Technology, BharatiVidyapeeth University College of Engineering, Pune-411043, India
  • Tai-hoon Kim Department of Convergence Security, Sungshin Women's University, 249-1, Dongseon-dong 3-ga, Seoul, 136-742, Korea

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