Zeta Disease Prediction

INTRODUCTION

Mars Mission Control needs a good data-driven system for predicting Zeta Disease infection on the International Mars Colony. Use the zeta-disease_training-data dataset to build a model that can predict who will be infected by Zeta Disease. Train and apply a classification model to the zeta-disease_prediction-data dataset to predict who will be infected by Zeta Disease.

DATASET

The dataset includes 9 columns with information on 800 people.

1. age : in years
2. weight : body weight in pounds (lbs)
3. bmi : Body Mass Index (weight in kg/(height in m)2)
4. blood_pressure : resting blood pressure (mm Hg)
5. insulin_test : inuslin test value
6. liver_stress_test : liver_stress_test value
7. cardio_stress_test : cardio_stress_test value
8. years_smoking : number of years of smoking
9. zeta_disease : 1 = yes; 0 = no

Results

• analysis.ipynb is the main notebook containing the code for training and testing the model. It is also available for viewing as a HTML under html-exports.
• The environment used to perform the analysis is provided as a conda environment file - zeta-env.yml.
• The data visulaizations are saved as HTML and are placed under html-exports folder.
• The final predictions are placed under predictions folder.