UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 3
March-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRAQ06076


Registration ID:
202099

Page Number

371-374

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Title

CLASSIFICATION TECHNIQUES BASED DATA MINING IN STUDENT PERFORMANCE PREDICTION

Abstract

In displayed models best classification algorithms in instructive data mining towards exhibiting predominant foreseeing models have been given. Dissect and approval done on models demonstrates the got outcomes are exact and dependable. In such manner individual, natural and instructive variables influencing successful and unsuccessful students have been examined and as per them proficient models dependent on choice tree strategies like c4.5 tree calculation, bolster vector machine techniques and calculated relapse have been displayed. The outcomes can help directors of instructive frameworks towards a right instructive arranging an advancing of instructive procedures in secondary schools. Assessment and expectation of students' execution in secondary school help to discover imperative variables influencing students' achievement in training and also they can have a vital job in helping instructive administrators in enhancing the nature of schools. As indicated by this reality that data mining science has dependably been a reasonable procedure to remove information from data, this can be utilized for giving a decent methodology. This article attempts to introduce prevalent models in foreseeing students' execution. The referenced data of this article are taken from 386 students of secondary schools in Bushehr territory.

Key Words

instructive data mining,c4.5 tree calculation, bolster vector machine techniques,datamining science

Cite This Article

"CLASSIFICATION TECHNIQUES BASED DATA MINING IN STUDENT PERFORMANCE PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.371-374, March-2019, Available :http://www.jetir.org/papers/JETIRAQ06076.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"CLASSIFICATION TECHNIQUES BASED DATA MINING IN STUDENT PERFORMANCE PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp371-374, March-2019, Available at : http://www.jetir.org/papers/JETIRAQ06076.pdf

Publication Details

Published Paper ID: JETIRAQ06076
Registration ID: 202099
Published In: Volume 6 | Issue 3 | Year March-2019
DOI (Digital Object Identifier):
Page No: 371-374
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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