To predict the health risk of pregnant women.
Link to the dataset: https://archive.ics.uci.edu/dataset/863/maternal+health+risk
There are 7 columns: Age, Systolic Blood Pressure, Diastolic Blood Pressure, Blood Sugar Level, Body Temperature, Heart Rate and Health Risk.
Health Risk has been classified into 3 risk levels: Low Risk, Mid Risk, High Risk.
Remove outliers and perform one-hot encoding on the 'Health Risk' column: Low Risk:0, Mid Risk:1, High Risk:2.
Random forest Classifier has been used to perform the task of classification, with the It is a supervised learning based model which uses RANDOM FOREST CLASSIFIER in order to make the prediction with an accuracy of 90.19%.
This project is still a work in progress to try implement ANN models in order to improve the accuracy.