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Published in:

Volume 5 Issue 12
December-2018
eISSN: 2349-5162

Unique Identifier

JETIRDZ06123

Page Number

950-957

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Title

Identifying factors affecting placement status of engineering students using explainable machine learning

ISSN

2349-5162

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"Identifying factors affecting placement status of engineering students using explainable machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.950-957, December 2018, Available :http://www.jetir.org/papers/JETIRDZ06123.pdf

Abstract

Machine learning (ML) models are increasing their penetration in different problem domains due to their increasing accuracy. Majority of the advanced ML-based stand high in predictive accuracy but are wanting in terms of explaining their outcomes. This research study has two objectives. First, to develop predictive models that can predict the placement status of undergraduate engineering students studying in India. Second, to understand the behavior of these ML-based models in terms of most important features affecting the prediction outcome. The outcomes of such study are of importance to any university as ability to anticipate placement status of students can help in planning timely interventions. It is concluded that ‘CurrentCGPA’ and ‘AttendancePercentage’ of a student plays an important role towards getting placed. Moreover, understanding of the behavior of a model help building trust in the model and provide multiple insights of importance to different stake holders.

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"Identifying factors affecting placement status of engineering students using explainable machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp950-957, December 2018, Available at : http://www.jetir.org/papers/JETIRDZ06123.pdf

Publication Details

Published Paper ID: JETIRDZ06123
Registration ID: 233506
Published In: Volume 5 | Issue 12 | Year December-2018
DOI (Digital Object Identifier):
Page No: 950-957
ISSN Number: 2349-5162

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Cite This Article

"Identifying factors affecting placement status of engineering students using explainable machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp950-957, December 2018, Available at : http://www.jetir.org/papers/JETIRDZ06123.pdf




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