Classifying Source Code Using Boosting Algorithms-Reference-Cited by-同舟云学术

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Classifying Source Code Using Boosting Algorithms

Published:2022-02-23 Issue: Volume: Page:
ISSN:
Container-title:2022 2nd International Conference on Advanced Research in Computing (ICARC)
language:
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Author:

Ifham Mohamed¹,Kumara B. T. G. S¹,Kuhaneswaran Banujan¹,Senthan Prasanth²,Ekanayake E. M. U. W. J. B³

Affiliation:

1. Sabaragamuwa University of Sri Lanka,Department of Computing and Information Systems,Belihuloya,Sri Lanka

2. Sabaragamuwa University of Sri Lanka,Department of Physical Sciences and Technology,Belihuloya,Sri Lanka

3. Uva Wellassa University of Sri Lanka,Department of Computer Science and Informatics,Sri Lanka

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9752770/9753716/09754084.pdf?arnumber=9754084

Reference16 articles.

1. VisioTM: A Tool for Visualizing Source Code Based on Topic Modeling

2. Latent dirichlet allocation;blei;The Journal of Machine Learning Research,2003

3. Mallet: A machine learning for language toolkit;mccallum,2002

4. Learning to classify short and sparse text & web with hidden topics from large-scale data collections

5. Semantic clustering: Identifying topics in source code

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