Polycystic Ovary Syndrome Analysis Using Machine Learning Algorithms
Keywords:Machine Learning, KNN Algorithm, Logistic Regression, SVM, Decision tree, Random forest, CatBoost Classifier
Polycystic ovary syndrome or PCOS is a hormone
A common disease among women of reproductive age. This
once diagnosed, it cannot be cured. Help to avoid its effects.
The exact cause of PCOS is still unknown. But there are
some factors that illustrate the possibility of PCOS. The
factors that cause this syndrome are : obesity and insulin,
immunity , blood pressure , depression , inflammation.
Symptoms include : hirsutism, oligo-ovulation, acne, heavy
bleeding, darkening of the skin. Causes and uses a model is
developed to accept the symptoms and their characteristics.
Machine Learning models used for supervised classification
are K-Nearest Neighbor and logistic regression. The reason
multiple models were built behind the scenes to identify the
best one for a given dataset , the known extent of