Polycystic Ovary Syndrome (PCOS) is a condition in which the ovaries produce an abnormal amount of androgens, male sex hormones that are usually present in women in small amounts. The name polycystic ovary syndrome describes the numerous small cysts that form in the ovaries. However, some women with the disorder do not have cysts, while some women without the disorder do develop cysts. Here, we will analyze data to understand which are possible influencers of PCOS. The dataset includes several variables, which are suspected to influence the chances of Polycystic ovary syndrome (PCOS).
The data source is : https://www.kaggle.com/datasets/prasoonkottarathil/polycystic-ovary-syndrome-pcos
This is my Sem -1 Regression Techniques project under respected professor Dr. Deepayan Sarkar at ISID.
Note: Due to some unavoidable circumstances all my code files got deleted and unfortunately I had no backup. Thus, there is no code file. I have used both
R and Python in RStudio. (Using reticulate)