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Kapoor, Nitika. Student's employability indexing using machine learning approach. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2022.
Student's employability indexing using machine learning approach
Name: Sharma, Parshant
Organization :
Chandigarh University. Department of Computer science and engineering
Email :
parshant88sharma@gmail.com
Name: Anand, Darpan
Organization :
Chandigarh University. Department of Computer science and engineering
Email :
darpan.anand.agra@gmail.com
Name: Kapoor, Nitika
Organization :
Chandigarh University. Department of Computer Science and engineering
Email :
nitika.cse@cumail.in
LCSH:
Employability
LCSH:
Machine learning
LCSH:
Education
-- Economic aspects
Abstract:
Predicting unemployment rates has
become crucial since it can assist
designing
governments in
strategies. making decisions and
Conventional univariate time series models and
econometric approaches for predicting unemployment
rates have garnered considerable attention from
governments, corporations, research institutes, and
academics in prior studies. Novel approaches for
forecasting unemployment rates based on search engine
query data have recently been developed. To help
comprehend how graduates are hired, four learning
algorithms were used: SVM, DT, XGBoost, RF. The
accuracy, precision, and recall metrics, as well as the f1-
score and support measures, were all assessed using the
efficiency matrix. During the studies, the Extreme
Gradient Boosting (XGBoost) achieved an accuracy
rate of 81.22 percent, which was much higher than all
of the learning algorithms, including SVM 79.6 percent,
study is quite DT 79.4 and RF 79.1 percent. This
promising, which has pushed the researchers to
improve the procedure and evaluate the developed
prediction model for further study.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2022
Modified:
2024-05-15
Issued:
2024-05-15
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Computer Society. 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT 2022) (pp.242-249). Los Alamitos, CA : IEEE Computer Society
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
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Sharma, Parshant
| Title | Contributor | Type |
|---|---|---|
| Student's employability indexing using machine learning approach
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Sharma, Parshant;Anand, Darpan ;Kapoor, Nitika | บทความ/Article |
Anand, Darpan
| Title | Contributor | Type |
|---|---|---|
| Student's employability indexing using machine learning approach
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Sharma, Parshant;Anand, Darpan ;Kapoor, Nitika | บทความ/Article |
Kapoor, Nitika
| Title | Contributor | Type |
|---|---|---|
| Student's employability indexing using machine learning approach
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Sharma, Parshant;Anand, Darpan ;Kapoor, Nitika | บทความ/Article |