This repository contains an example of reducing overfitting in perdiction in decision trees

Overview

Overfitting it's when the model fails to generalize well to the new data. In this example we solved the overfitting by manipulating the

Contents

• quiz.ipynb: Jupyter Notebook containing the implementation of solving overfitting in decision trees using Python.
• heart_failure_clinical_records-sample.csv.csv: Sample dataset used in the notebook for demonstration purposes.
• README.md: This file providing an overview of the repository.

Requirements

To run the code in the Jupyter Notebook, you need to have Python installed on your system along with the following libraries:

• NumPy
• pandas
• scikit-learn

You can install these libraries using pip:

pip install numpy pandas scikit-learn

Usage

1. Clone this repository to your local machine:

git clone https://github.com/BaraSedih11/ReducingOverfitting.git

2. Navigate to the repository directory:

cd ReducingOverfitting

3. Open and run the Jupyter Notebook quiz.ipynb using Jupyter Notebook or JupyterLab.

4. Follow along with the code and comments in the notebook to understand how to solve overfitting using Python.

Acknowledgements

• scikit-learn: The scikit-learn library for machine learning in Python.
• NumPy: The NumPy library for numerical computing in Python.
• pandas: The pandas library for data manipulation and analysis in Python.