The following repository contains code for the classification of Low Birth Weight of babies.
The methods uses are:
- K-Nearest Neighbours
- Decision Trees
- Gaussian Naive Bayes
The first method is present in a folder labeled knn and can be run using the command python3 knn.py. The other files are used for benchmarking accuracy.
The second method is present as an interactive jupyter notebook. It can be run using a modern text editor such as VS Code.
The third method is present as an exported Google Colab notebook. It can be run natively using python3 or exported to Google Colab and run. The can be found in the report.
Additionally, a folder labeled data contains all of the cleaned data. The sets of data represent different versions of the same. Final.csv co-incidentally contains the data used for classification.
A folder labeled out contains some data for knn used for benchmarking accuracy.
A folder labelled plots contains the scripts and images of the various plots used to visualize the data and classifications.
A folder labeled res contains the resources such as Dr. Snehanshu Saha's paper on the same problem and our report. (WIP)