N B Interpolation Technique for Improved Arbitrarily missing values in Data Mining

Authors

  • Dr. Darshanaben Dipakkumar Pandya  Assistant Professor, Department of Computer Science, Shri C.J Patel College of Computer Studies (BCA), Visnagar, Gujarat, India
  • Dr. Abhijeetsinh Jadeja  Principal(I/C), Department of Computer Science, Shri C.J Patel College of Computer Studies (BCA), Visnagar, Gujarat, India
  • Dr. Sheshang D. Degadwala  Head of Computer Department, Sigma Institute of Engineering, Vadodara, Gujarat, India

DOI:

https://doi.org//10.32628/IJSRSET229217

Keywords:

Data Mining, Interpolation, Newton’s Backward Interpolation Formula, Numerical Data.

Abstract

In data mining in order to reduce the numerical computations associated to the repeated application of the existing interpolation formula in computing a large number of interpolated values, a formula has been derived from Newton’s backward interpolation formula for representing the numerical data on a arbitrarily missing vales in database. A suit approach of the formula to numerical data has been shown in the case of representing the data on the dataset global carbon dioxide emissions from fossil fuel burning by Fuel Type corresponding as a method of time. The formula is suitable in the situation where the values of the argument are at equal interval.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-04-30

Issue

Volume 9, Issue 2, March-April-2022

Section

Research Articles

License

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

How to Cite

[1]
Dr. Darshanaben Dipakkumar Pandya, Dr. Abhijeetsinh Jadeja, Dr. Sheshang D. Degadwala, " N B Interpolation Technique for Improved Arbitrarily missing values in Data Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 2, pp.79-85, March-April-2022. Available at doi : https://doi.org/10.32628/IJSRSET229217