An Applied Secant Method for Recovered Missing Mass 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/CSEIT22823

Keywords:

Data Mining, Missing Sequential Bulk Values, An Applied Secant Method

Abstract

In data mining, the preparation of complete, quality and real data is a key prerequisite for successful data mining in order to discover something new from data already recorded in a given database. Data preparation for data extraction is a fundamental step in data analysis. Data with missing values complicate both data analysis and application of a new data solution. To overcome this situation, some Numerical techniques must be used during data preparation. With the help of Numerical and technical methods, we can retrieve the incomplete state of missing data in huge sequential values and reduce ambiguities using an applied Secant method. In this article, we present a sequential method by which the values of the missing attribute are replaced by the best adapted value.

References

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

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Published

2022-04-30

Issue

Volume 8, Issue 2, March-April-2022

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]
Dr. Darshanaben Dipakkumar Pandya, Dr. Abhijeetsinh Jadeja, Dr. Sheshang D. Degadwala, " An Applied Secant Method for Recovered Missing Mass Values in Data Mining " International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 2, pp.97-103, March-April-2022. Available at doi : https://doi.org/10.32628/CSEIT22823