Fuzzy rule based decision trees

@article{Wang2015FuzzyRB,
  title={Fuzzy rule based decision trees},
  author={Xianchang Wang and Xiaodong Liu and Witold Pedrycz and Lishi Zhang},
  journal={Pattern Recognition},
  year={2015},
  volume={48},
  pages={50-59}
}
This paper presents a new architecture of a fuzzy decision tree based on fuzzy rules – fuzzy rule based decision tree (FRDT) and provides a learning algorithm. In contrast with “traditional” axis-parallel decision trees in which only a single feature (variable) is taken into account at each node, the node of the proposed decision trees involves a fuzzy rule which involves multiple features. Fuzzy rules are employed to produce leaves of high purity. Using multiple features for a node helps us… CONTINUE READING
Highly Cited
This paper has 29 citations. REVIEW CITATIONS
17 Citations
40 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 17 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 40 references

Best-first decision tree learning (Ph.D

  • H. Shi
  • thesis), Citeseer,
  • 2007
Highly Influential
7 Excerpts

Amblard , Classi fi cation trees for time series

  • C. A. Douzal-Chouakria
  • Pattern Recognit .
  • 2012

Similar Papers

Loading similar papers…