This repository contains machine and deep learning implementations for classification and regression tasks. The featured models, including neural networks (2x), linear regression, and logistic regression, are designed to predict target variables based on input variables. The process involves training the models, assessing the outcomes, and storing the performance metrics in a table. For these models to work, you'll need a CSV file with both predictors and outcomes in wide format. The output is a table which is saved as a CSV file.
In addition, there are examples provided on how to use these classes. Please note that this is the initial implementation, and the file paths are currently set as absolute paths.
This work has been used in the author's Doctoral thesis (Health Data Science).