Hybrid Fused Algorithms for the Prediction of Feedback in the Education Systems

Authors

  • Kirankumar G Sutar
  • Mahadev S Patil

DOI:

https://doi.org/10.65000/63cgf576

Keywords:

Machine learning, Support Vector Machine, Map Reduce Algorithm, feedback, education system

Abstract

Student achievement expectations assist educational partners in making proactive decisions and resolving conflicts in terms of improving the nature of coaching and suit current societal unique needs. The verification of components for an understudy's display figure not only plays an important role in increasing assumption precision, but it also aids in the development of fundamental plans for the improvement of an understudy's educational show.There are distinctive component choice calculations for foreseeing the presentation of understudies, but the examinations revealed in the writing guarantee that there are various upsides and downsides of existing element determination calculations in choice of ideal elements.In the proposed hybrid framework fused the Support Vector Machine and Map reduce algorithm to predict the feedback in the education system. Framework, it gives ML Algorithm to viable forecast of different sickness events in illness successive social orders. Contrasted with a few average estimate algorithms, the computation precision of our proposed calculation comes to 94.8% with assembly speed. 

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Published

31-12-2021

Issue

Section

Articles

How to Cite

Sutar, K. G., & Patil, M. S. (2021). Hybrid Fused Algorithms for the Prediction of Feedback in the Education Systems. International Journal of Modern Computation, Information and Communication Technology, 4(11 & 12), 61-67. https://doi.org/10.65000/63cgf576