This repository contains the code and notebooks developed for the practical work of Computational Intelligence. The project was implemented using Python and Jupyter Notebooks.
-
module.py
: This file contains the auxiliary functions needed to develop each of the experiments, including:- Functions that implement the algorithms.
- Functions that generate data.
- Functions that calculate the error.
- Functions that represent the target.
-
Notebooks:
perceptron.ipynb
: Contains the implementation and experiments with the Perceptron algorithm.regression_linear.ipynb
: Contains the implementation and experiments with the Linear Regression algorithm.regression_nonlinear.ipynb
: Contains the implementation and experiments with Nonlinear Data and tranformations.pocket_pla.ipynb
: Contains the implementation and experiments with the Pocket PLA (Perceptron Learning Algorithm).
To run the notebooks, make sure you have the following Python packages installed:
- NumPy
- Matplotlib
- Jupyter
You can install these packages using pip
:
pip install numpy pandas matplotlib jupyter
- Clone this repository:
git clone https://github.com/username/repository.git
- Navigate to the repository directory:
cd repository
- Start Jupyter Notebook:
jupyter notebook
- Open one of the notebooks (
perceptron.ipynb
,regression_linear.ipynb
,regression_nonlinear.ipynb
, orpocket_pla.ipynb
) and run the cells to view the experiments and results.
Contributions are welcome! If you have suggestions or improvements, please open an issue or submit a pull request.
Special thanks to Professor Pedreira and the TA Vinicius Costa for their support and guidance throughout this project.
This project is licensed under the MIT License - see the LICENSE file for details.