Classification for predicting PCOS Using Red Deer Algorithm with XGBoost Classifier

Author(s)	J Fathima Kaleema, D Usha Rani
Country	India
Abstract	Polycystic Ovary Syndrome (PCOS) is a hormonal imbalance disorder that has common among women reproductive age. It affects 20% of women of bearing age. PCOS affected the age between 15-44 .PCOS enlarge ovaries with small cysts in the ovaries. It can lead to unregulated hormonal cycle and also trigger periods , high blood pressure, diabetes, acne, Infertility and growth of hair on face , PCOS cause type 2 diabetes. In this paper propose combination of red deer algorithm with XGBoost algorithm to classify and predict the earlier stage of ovaries to diagnosis and treatment can be used to prevent the long-term problems.
Keywords	PCOS, Type 2 Diabetes ,Red Deer Algorithm, XGBoost.
Field	Computer Applications
Published In	Volume 6, Issue 4, July-August 2024
Published On	2024-08-22
Cite This	Classification for predicting PCOS Using Red Deer Algorithm with XGBoost Classifier - J Fathima Kaleema, D Usha Rani - IJFMR Volume 6, Issue 4, July-August 2024. DOI 10.36948/ijfmr.2024.v06i04.25966
DOI	https://doi.org/10.36948/ijfmr.2024.v06i04.25966
Short DOI	https://doi.org/gt8g7p

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