Decision Tree ID3 Algorithm Based on Rough Set
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    Abstract:

    Aiming at solving the problem that the traditional ID3 algorithm is complicated and there exists redundancy information, this study proposes an improved algorithm—attribute reduct simplified ID3 algorithm based on rough set. This algorithm uses the properties of attribute reduct in rough set to delete the redundant knowledge, and makes the classification system more concise with the same classification ability. At the same time, it simplifies the entropy formula with Taylor formula to make the calculation easier. And then this study applies the improved algorithm to the example, and uses the massive data in the related database to program in order to do simulation experiments. Finally, the simulation results proved the correctness and feasibility of the proposed algorithm. It can not only reduce the information duplication, reduce the redundancy rules, but also ensure the accuracy of the algorithm. At the same time, it provides a certain reference value for the better application of ID3 algorithm to real life examples.

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余建军,张琼之.基于粗糙集的决策树ID3算法.计算机系统应用,2020,29(4):156-162

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History
  • Received:August 12,2019
  • Revised:September 06,2019
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  • Online: April 09,2020
  • Published: April 15,2020
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