statistical learning spring 2023
Using decision trees and naive bayes to classify maternal health risk using the dataset from UCI Machine Learning Repository. Dataset Link
The data was collected from different hospitals, community clinics, and maternal health centers from the rural areas of Bangladesh through the IoT based risk monitoring system. See the inlcuded report PDF where I include details of the project and my output.
| Variable | Description |
|---|---|
| Age | Any ages in years when a woman is pregnant |
| SystolicBP | Upper value of Blood Pressure in mmHg |
| DiastolicBP | Lower value of Blood Pressure in mmHg |
| BS | Blood glucose levels in terms of molar concentration, mmol/L |
| BodyTemp | Body Temperature in F |
| HeartRate | Normal heart rate in beats per minute |
| Risk Level | Predicted Risk Intensity level during pregnancy |