This repository hosts the project files for the development of a final AI project built as part of coursework assignments focusing on supervised learning techniques. The primary objective of this project is to explore the implementation of ensemble models to solve regression and classification problems.
It was developed as part of the Artificial intelligence discipline at Federal University of Alfenas.
In this activity, the goal is to create an AI model using ensemble methods to solve a problem that requires supervised training, taking into account the topics studied in the course.
The main objectives of this activity are
- To assess the importance/effect of model combination in regression/classification problems.
- To evaluate the impact of different training datasets on the performance of the combined model (note that the test set must remain fixed and separate from the training set).
- To identify the advantages and disadvantages of using ensemble models.
For this project, we utilized datasets for both classification and regression tasks: