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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21502
Article Published : 8513
Total Authors : 22399
Total Reviewer : 805
Total Countries : 158
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| Paper Title: | Analysis of Students’ Performance Using Ensemble Stacking Technique |
| Authors Name: | Dr.Ashok M.V , Dr.Safira Begum |
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| Author Reg. ID: |
IJRTI_189683
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| Published Paper Id: | IJRTI2404121 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | The advent of smartphone and internet has enabled the enormous amount of data being created and collected on a daily basis, such data is referred as Big Data. Analyzing such huge datasets to find correlations or patterns becomes challenging due to the complex nature of data, multiple features associated with data and the quantum of data. Extracting hidden knowledge from the data is possible through the Data mining techniques, which is also known as knowledge discovery or information discovery. Educational Data mining refers to techniques that can be applied to identify patterns from educational datasets. The purpose of this research study is to evaluate and predict the performance of engineering students with ensemble capabilities in the orange tool. As part of the study a group of undergraduate students academic and demographic factors are collected. The gathered students’ data was used to build predictive models using traditional classifiers namely, K-Nearest Neighbor, Decision Tree, Random Forest. Further, the ensemble method stacking, which is known for improving the performance of individual classifier is implemented. The result revealed that the Area Under the Curve score, accuracy, precision, recall, and F1 score is considerably improved by using ensemble stacking in comparison to that of each of the three individual classifiers. |
| Keywords: | Educational Data Mining, Prediction, Classification Model, Ensemble method, Stacking |
| Cite Article: | "Analysis of Students’ Performance Using Ensemble Stacking Technique", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.875 - 879, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404121.pdf |
| Downloads: | 000205254 |
| 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: IJRTI2404121
Registration ID:189683
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 875 - 879 Country: Bangalore, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404121 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404121 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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