UGC Approved Journal no 63975(19)

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

Volume 6 Issue 4
April-2019
eISSN: 2349-5162

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

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Published Paper ID:
JETIRBI06008


Registration ID:
208213

Page Number

41-46

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Title

Improvising multinomial Classification Accuracy of the model using Feature Selection and Class Imbalance algorithms

Abstract

Higher education institutions across the globe are tirelessly making efforts to improvise the student performance and curb down the attrition rates. Academic institutions hold a massive amount of information like students personal details, classroom activities, academic achievements, etc., Thus obtaining insights from this data is highly imperative to take crucial decisions for education institutions. Embracing technology is the only solution to address these challenges and this in turn attributed to the usage of Education Data Mining. In this research work, we made a conscious effort to predict the performance of students using various attributes like socioeconomic, academic and demographic details. To overcome the class imbalance problem, we applied the Synthetic Minority Over-sampling Technique (SMOTE) technique. We conducted Pearson's Chi-Squared Test to identify important attributes and Ensemble methods were used to build the prediction model. The results showed that Random Forest performed better than the Bagging and Boosting models.

Key Words

SMOTE, Chi-Square Test, Random Forest, Bootstrap Aggregation, AdaBoost

Cite This Article

"Improvising multinomial Classification Accuracy of the model using Feature Selection and Class Imbalance algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.41-46, April-2019, Available :http://www.jetir.org/papers/JETIRBI06008.pdf

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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

"Improvising multinomial Classification Accuracy of the model using Feature Selection and Class Imbalance algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp41-46, April-2019, Available at : http://www.jetir.org/papers/JETIRBI06008.pdf

Publication Details

Published Paper ID: JETIRBI06008
Registration ID: 208213
Published In: Volume 6 | Issue 4 | Year April-2019
DOI (Digital Object Identifier):
Page No: 41-46
Country: -, -, -- .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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