C5 Causal Decision Tree

Authors

  • S. Arul Selvi  Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • S. Sowmiya  Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • R. Sangeetha  Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India

Keywords:

Decision tree, Causal relationship, Potential outcome model, Partial association

Abstract

A choice tree is fabricated best down from a root hub and includes apportioning the information into subsets that contain examples with comparative esteems (homogenous). On the off chance that the example is totally homogeneous the entropy is zero and if the example is a similarly partitioned it has entropy of one. C5.0 calculation and blue line demonstrates proposed calculation. With the assistance of diagram we can see that exactness of enhanced C5.0 is high when the information estimate is less. In any case, precision of C5.0 calculation diminishes with the expansion of information measure. Exactness of proposed show is superior to anything C5.0 for expansive information estimate.

References

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  5. J. Pearl, Causality: Models, Reasoning, and Inference, 2nd ed. Cambridge University Press, 2009.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
S. Arul Selvi, S. Sowmiya, R. Sangeetha, " C5 Causal Decision Tree" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.876-879, March-April-2018.