The aim of this project is to build a model capable of predicting if a patient will survive or not to a Boolean pandemic that had its origin in the state of New Mexico. For this purpose, a wide set of machine learning algorithms and grid search procedures were tested on the available data with the intent of finding the most relevant features and the best combination of data encoders and model hyperparameters. In the end, and as expected, the Multi-layer Perceptron algorithm was the one that provide the overall better results and, in some particular cases, the ensemble with the help of either the Vote Classifier or the Stacking Classifier also enhanced the final results. For the given data, and bearing in mind their limited size, the transformation or creation of new features often played a major role on the final accuracy of the model.
The project description can be consulted at: https://bit.ly/2XL4wX8
Project Format: Python File (.py)
Project Maximum Size: None
Beginning Date: 25th April 2020
Due Date: 31th May 2020
Members:
- davidsousa98
- miguelramos0703
- RFlorindo