Improving Efficiency in High Dimensional Datasets Using Booster

Authors

  • Dharmavaram Maheshkumar  Computer Science Deportment, Mallareddy Enginerring College(MREC), Hyderabad, Telangana, India
  • Jasti Sireesha  Associate Professor, Computer Science Deportment, Mallareddy Enginerring College(MREC), Hyderabad, Telangana, India

Keywords:

Accuracy, Prediction algorithms, Redundancy, Q-statistic, FS, Booster

Abstract

The information retrieving in high dimensional data with the couple of recognitions is winding up more run of the mill, especially in microarray data. In the middle of the latest twenty years, heaps of doable/possible game plan Flows and FS calculations, this is higher for proposed to educated guess rightness, the result of an FS calculation with (thinking about/when one thinks about) desire (quality of being done perfectly or being totally correct) can be unsteady among the mixed groups of things in the readiness set, especially with high dimensional data. This paper recommends another (process of figuring out the worth, amount, or quality of something) count Q-measurement that combines the strength and health of the picked incorporate subset (even though there is the existence of) the estimate (quality of being very close to the truth or true number). By then and the (happening sometime in the future) (the) unavoidable, already-decided future of the Booster of an FS calculation that lifts the guess of Q-measurement of the count connected. (Related to watching or recording something) examinations show that Booster helped in the guess of the Q-measurement and also the desired (high) quality of the count connected unless the (teaches things) list is clearly very hard to suspect with the given calculation.

References

  1. M. Abdalla, P. A. Fouque, and D. Pointcheval. Password-based authenticated key exchange in the three-party setting. In Proc. PKC’05, pages 65-84, 2005.
  2. https://crypto.stanford.edu/pbc/download.html
  3. https://gmplib.org
  4. https://tls.mbed.org
  5. M. Abdalla and D. Pointcheval. Simple password-based encrypted key exchange protocols. In Proc. CT-RSA 2005, pages 191-208, 2005.
  6. M. Bellare, D. Pointcheval, and P. Rogaway. Authenticated key exchange secure against dictionary attacks. In Proc. Eurocrypt’00, pages 139-155, 2000.
  7. S. M. Bellovin and M. Merritt. Encrypted key exchange: Password-based protocol secure against the dictionary attack. In Proc. 1992 IEEE Symposium on Research in Security and Privacy, pages 72-84, 1992.
  8. J. Bender, M. Fischlin, and D. Kugler. Security analysis of the PACE key-agreement protocol. In Proc. ISC’09, pages 33-48, 2009.
  9. J. Bender, M. Fischlin, and D. Kugler. The PACE|CA protocol for machine-readable travel documents. In INTRUST’13, pages 17-35, 2013.
  10. D. Boneh and M. Franklin. Identity-based encryption from the Weil pairing. In Proc. Crypto'01, pages 213-229, 2001.
  11. V. Boyko, P. Mackenzie, and S. Patel. Provably secure password authenticated key exchange using Diffie-Hellman. In Proc. Euro- crypt’00, pages 156-171, 2000.
  12. J. Brainard, A. Juels, B. Kaliski, and M. Szydlo. Nightingale: A new two-server approach for authentication with short secrets. In Proc.12th USENIX Security Symp., pages 201-213, 2003.

International Journal of Scientific Research in Science and Technology

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Published

2018-04-30

Issue

Volume 4, Issue 7, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

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

How to Cite

[1]
Dharmavaram Maheshkumar, Jasti Sireesha, " Improving Efficiency in High Dimensional Datasets Using Booster, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 7, pp.305-309, March-April-2018.