ARCHIVES
Research Article
Detecting Autism Spectrum Disorder Using Machine Learning Techniques
Madhanraj T1
Tharun V2
Vishnu Kumar R3
Divya P4
1234 Computer science and engineering, Bannari Amman Institute of Technology, Tamilnadu, India
Published Online: March-April 2023
Pages: 08-11
Cite this article
No DOIReferences
[1] "A framework for clustering evolving data streams," by C. C. Aggarwal, J. Han, J. Wang, and P. S. Yu, in Proceedings of the
International Conference on Very Large Data Bases (VLDB '03), 2019, pages 81–92.
[2] Data stream clustering: A study by J. A. Silva, E. R. Faria, R. C. Barros, E. R. Hruschka, A. C. P. L. F. d. Carvalho, and J. A.Gama,
A survey,” volume of ACM Computing Surveys 46, no. 1, pp. 13:1–13:31, Jul. 2019.
[3] "Density-based clustering over an evolving data stream with noise," by F. Cao, M. Ester, W. Qian, and A. Zhou, in Proceedingsof the
2006 SIAM International Conference on Data Mining. Pages SIAM, 2019, 328–339.
[4] "Density-based clustering for real-time stream data," by Y. Chen and L. Tu, is published in the Proceedings of the 13th ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining. USA: New York, NY: ACM, 2019, pp. 133–142.
[5] "Stream data clustering based on grid density and attraction," by L. Tu and Y. Chen, in ACM Transactions on Knowledge
Discovery from Data, vol. 3, no. 3, pp. 1–27, 2019.
International Conference on Very Large Data Bases (VLDB '03), 2019, pages 81–92.
[2] Data stream clustering: A study by J. A. Silva, E. R. Faria, R. C. Barros, E. R. Hruschka, A. C. P. L. F. d. Carvalho, and J. A.Gama,
A survey,” volume of ACM Computing Surveys 46, no. 1, pp. 13:1–13:31, Jul. 2019.
[3] "Density-based clustering over an evolving data stream with noise," by F. Cao, M. Ester, W. Qian, and A. Zhou, in Proceedingsof the
2006 SIAM International Conference on Data Mining. Pages SIAM, 2019, 328–339.
[4] "Density-based clustering for real-time stream data," by Y. Chen and L. Tu, is published in the Proceedings of the 13th ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining. USA: New York, NY: ACM, 2019, pp. 133–142.
[5] "Stream data clustering based on grid density and attraction," by L. Tu and Y. Chen, in ACM Transactions on Knowledge
Discovery from Data, vol. 3, no. 3, pp. 1–27, 2019.
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