Theoretical Study of Predictive Model Using Data Mining Technique on Academic Dataset

Authors

  • Pooja Singh   Department of Computer Science, Sudarshan College, Lalgaon, Awadhesh Pratap Singh University Rewa, Madhya Pradesh, India
  • Dr. G. N. Singh   Department of Computer Science, Sudarshan College, Lalgaon, Awadhesh Pratap Singh University Rewa, Madhya Pradesh, India
  • Dr. Arvind Singh    Department of Computer Science, Sudarshan College, Lalgaon, Awadhesh Pratap Singh University Rewa, Madhya Pradesh, India

Keywords:

Gymnema sylvestre R. Br., diabetes, Callus induction, proliferation, biochemical analysis.

Abstract

The basic purpose of an educational system's must be to prepare successful careers of students within a predetermined time period. In Present scenario economics and society is directly and indirectly linked to the effectively with educational systems by which can achieve goal. Education is a critical part of every Country and all over the world’s community's overall their growth and development. To maintain and ensure the data associated with the educational institution is correctly analyzed. Many important insights which can give contribution to the continuous improvement of students in the future. Through Data mining and machine learning that are most important equipment to achieve this goal because there are various approaches that aid in finding that crucial information from that huge amount of data and databases [1]. In data mining process which employs a variety of methods that applies during the operation, such as clustering, association and classification as well as rule mining in order to fetch previously cryptic information from a database. Data mining technique is the very efficient and effective method which is used in the data analytics for measuring performance by creating models and algorithms.

References

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Published

2021-04-10

Issue

Section

Research Articles

How to Cite

[1]
Pooja Singh, Dr. G. N. Singh, Dr. Arvind Singh , " Theoretical Study of Predictive Model Using Data Mining Technique on Academic Dataset, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 9, Issue 1, pp.1382-1388, March-April-2021.