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fco3lho/regression_and_classification_models

Training and evaluation of regression and classification models using ready-made datasets. Experiments include splitting the data into training and testing, applying multiple algorithms (such as Linear Regression, Random Forest, XGBoost, SVM, among others) and comparing performance with metrics such as RMSE, Accuracy, F1-Score and ROC-AUC Curve.

How to execute

$ python3 -m venv venv
$ source venv/bin/activate
$ pip install -r requirements.txt
$ python3 -m ipykernel install --user --name=regression
$ jupyter notebook

After following the steps above, the link to access the Jupyter Notebook will be displayed in your terminal. Enter this URL when selecting the Kernel of your Notebook and execute the tasks.

Make sure you have the following extensions in VSCode: ms-toolsai.jupyter, ms-toolsai.jupyter-renderers, ms-toolsai.jupyter-keymap, and jithurjacob.nbpreviewer

If you have any questions, access this link to run in VSCode.

Contributors

FC
Created February 8, 2025
Updated February 21, 2025