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Axiomatic fuzzy set theory-based fuzzy oblique decision tree with dynamic mining fuzzy rules

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Abstract

This paper proposes a novel classification technology—fuzzy rule-based oblique decision tree (FRODT). The neighborhood rough sets-based FAST feature selection (NRS_FS_FAST) is first introduced to reduce attributes. In the axiomatic fuzzy set theory framework, the fuzzy rule extraction algorithm is then proposed to dynamically extract fuzzy rules. And these rules are regarded as the decision function during the tree construction. The FRODT is developed by expanding the unique non-leaf node in each layer of the tree, which results in a new tree structure with linguistic interpretation. Moreover, the genetic algorithm is implemented on \(\sigma \) to obtain the balanced results between classification accuracy and tree size. A series of comparative experiments are carried out with five classical classification algorithms (C4.5, BFT, LAD, SC and NBT), and recently proposed decision tree HHCART on 20 UCI data sets. Experiment results show that the FRODT exhibits better classification performance on accuracy and tree size than those of the rival algorithms.

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Acknowledgements

We are very grateful to all the anonymous editors and reviewers, as well as to all the co-authors for their contributions. Moreover, we would like to acknowledge the National Natural Science Foundation of China (61433004, 61627809, 61621004), and the Liaoning Revitalization Talents Program (XLYC1801005).

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Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China

    Yuliang Cai & Shaoxin Sun

  2. College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning, China

    Huaguang Zhang

  3. School of Sciences, Dalian Ocean University, Dalian, Liaoning, China

    Xianchang Wang

  4. College of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China

    Qiang He

Authors
  1. Yuliang Cai
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  2. Huaguang Zhang
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  3. Shaoxin Sun
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  4. Xianchang Wang
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  5. Qiang He
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Correspondence to Huaguang Zhang.

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Cai, Y., Zhang, H., Sun, S. et al. Axiomatic fuzzy set theory-based fuzzy oblique decision tree with dynamic mining fuzzy rules. Neural Comput & Applic 32, 11621–11636 (2020). https://doi.org/10.1007/s00521-019-04649-0

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  • DOI: https://doi.org/10.1007/s00521-019-04649-0

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