Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification-Reference-Cited by-同舟云学术

Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification

Published:2023 Issue: Volume: Page:25-33
ISSN:2367-3370
Container-title:Intelligent Computing and Networking
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Author:

Joshi Raunak,Gupta Abhishek,Soni Himanshu,Laban Ronald

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-0071-8_3

Reference35 articles.

1. Marshall G, Jonker L (2011) An introduction to inferential statistics: a review and practical guide. Radiography 17

2. Sarker IH (2021) Machine learning: algorithms, real-world applications and research directions. SN Comput Sci 2(3):1–21

3. Ndefo UA, Eaton A, Green MR (2013) Polycystic ovary syndrome: a review of treatment options with a focus on pharmacological approaches. Pharmacy Therap 38(6):336

4. Cormack RM (1971) A review of classification. J Roy Stat Soc Ser A (Gen) 134(3):321–367. http://www.jstor.org/stable/2344237

5. Kumari R, Srivastava SK (2017) Machine learning: a review on binary classification. Int J Comput Appl 160(7):11–15. https://doi.org/10.5120/ijca2017913083, http://www.ijcaonline.org/archives/volume160/number7/27084-2017913083

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