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International Journal of Scientific Development and Research - IJSDR
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Authors Name: Shiwani suryawanshi , Vinaya patil , Mayur saner , Viplav patil , Bhushan sarode
Unique Id: IJSDR1706021
Published In: Volume 2 Issue 6, June-2017
Abstract: Students opting engineering as their disciple is increasing rapidly. But due to various factors and inappropriate primary education in India dropout rates are high. Students are unable to excel in core engineering subjects which are complex and mathematical, hence mostly get drop / keep term (kt) in that subject. With the help of data mining techniques we can predict the performance of students in terms of grades and dropout for a subject can be predicted. In the proposed system, Naïve Bayes algorithm is used. Based on the rules obtained from the developed technique, the system can derive the key factors influencing student performance.
Keywords: dropout, prediction, classification, data mining, education.
Cite Article: "STUDENT PERFORMANCE PREDICTION USING CLASSIFICATION DATA MINING TECHNIQUES", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.2, Issue 6, page no.163 - 167, June-2017, Available :http://www.ijsdr.org/papers/IJSDR1706021.pdf
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Publication Details: Published Paper ID: IJSDR1706021
Registration ID:170496
Published In: Volume 2 Issue 6, June-2017
DOI (Digital Object Identifier):
Page No: 163 - 167
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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