Life Expectancy Predictor

An analysis on the performance and optimization of various classification ML models.
This project implements each of them, using several optimized parameters to predict someone's life expectancy (or if they will live for 2+ years) based on their current health and habits.

Attached are both a Python file and an identical Jupyter Notebook, as well as the training and testing CSV file for it.

Running

Prerequisites

• Python 3.x

Installing Libraries

To run this project, you will need the following libraries:

• pandas
• scikit-learn
• matplotlib
• seaborn
• tensorflow
• numpy

To install all of these at once, run the following command:

pip install pandas scikit-learn matplotlib seaborn tensorflow numpy

If this does not work, try making sure you have pip installed, or using pip3 instead

Testing code individually

Use the Jupyter Notebook to run cells individually, allowing to see how each individual model performs at a time.
IMPORTANT: Be sure to restart the Kernal before testing other models, to ensure that they are not being fit on previous models beforehand