Comparison of Data Mining Classification Method for Predicting Crop Water Requirement

Authors

  • Navtej Bhatt  MCA Department, Smt. V.B.Nandola MCA College, Bhacha, Gujarat, India
  • Dr. P.V.Virparia  G.H.Patel Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India

Keywords:

Data Mining, Decision Tree, Crop Water Requirement

Abstract

In this paper, we have compared different data mining classification algorithm. Out of many decision tree algorithm, we have selected J48, DecisionStump, RAPTree and RandomTree. All the information we have collected from our study area are first preprocessed and it is converted into ARFF file. We have used open source tool Weka for comparison and presented the result. Based on the result, we have concluded that RandomTree gives best performance on our Data.

References

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

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Published

2018-04-30

Issue

Volume 3, Issue 5, May-June-2018

Section

Research Articles

License

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Creative Commons License

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

How to Cite

[1]
Navtej Bhatt, Dr. P.V.Virparia, " Comparison of Data Mining Classification Method for Predicting Crop Water Requirement , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.34-40, May-June-2018.