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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2025
Volume 10 | Issue 5
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Impact Factor : 8.14
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| Paper Title: | Student Grade Analysis And Prediction Using Machine Learning Algorithms |
| Authors Name: | Syed Abubakar S , Raghavendra R |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_181538
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| Published Paper Id: | IJRTI2105023 |
| Published In: | Volume 6 Issue 5, May-2021 |
| DOI: | |
| Abstract: | The possibility to predict the basic performance of the students is very necessary to enhance their training skills. It has become a beneficial statistics that may be used for quite a number purposes. This paper encloses the advantage of documents mining techniques to predict the final grades of students especially based on their necessary total data. In the practical studies, three data mining techniques had been working on two academic datasets associated to arithmetic lesson and Portuguese language lesson. The outcomes validated the success of data mining getting to be aware of the techniques all through the prediction of student’s performances. Performing the prediction of scholar’s performance grew to become an important wish in many of the schools and institutes. The needed command to assist the risk of the students and provide guarantee to their maintenance, as long as the first class tutoring assets and knowledge , and enhancing the institute’s rating and popularity. But, which will be hard to execute for beginning to medium institute, in particular those who are limited in graduation and publish graduating programs, and they may have less number of students’ data for processing. So, the most purpose of the estimate is to point out the chance of coaching and modelling the dataset of small dimension and achievable of developing a template of prediction with reliable perfection outcome rate. The lookup search out of the key indications within the less number of dataset, it can be utilized in developing the forecast model, the usage of schematic and grouping algorithms. The first class symptoms had been needed into a numerous algorithms to think about the foremost correct model. With the chosen algorithms, the outcomes showed the capacity of grouping algorithm in deciding key symptoms in less number of datasets. |
| Keywords: | prediction, student’s performance, machine learning, artificial neural networks and deep learning. |
| Cite Article: | "Student Grade Analysis And Prediction Using Machine Learning Algorithms", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.6, Issue 5, page no.103 - 107, May-2021, Available :http://www.ijrti.org/papers/IJRTI2105023.pdf |
| Downloads: | 000204861 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2105023
Registration ID:181538
Published In: Volume 6 Issue 5, May-2021
DOI (Digital Object Identifier):
Page No: 103 - 107 Country: Bangalore, Karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2105023 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2105023 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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