https://github.com/udacity-machinelearning-internship/reducingoverfitting

Reducing overfitting in perdiction in decision trees
https://github.com/udacity-machinelearning-internship/reducingoverfitting

decision-trees overfitting overfitting-reduced pandas scki

Last synced: 9 months ago
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Reducing overfitting in perdiction in decision trees

• Host: GitHub
• URL: https://github.com/udacity-machinelearning-internship/reducingoverfitting
• Owner: Udacity-MachineLearning-Internship
• Created: 2024-05-18T17:05:34.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-05-21T20:27:45.000Z (over 1 year ago)
• Last Synced: 2025-01-21T08:24:10.259Z (11 months ago)
• Topics: decision-trees, overfitting, overfitting-reduced, pandas, scki
• Language: Jupyter Notebook
• Homepage:
• Size: 20.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          


![Reducing_Overfitting](https://github.com/BaraSedih11/ReducingOverfitting/assets/98843912/a55bce4b-223a-4c62-9a32-b2c78ee1abb1)

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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:

```bash

pip install numpy pandas scikit-learn

```

## Usage

1. Clone this repository to your local machine:

```bash

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

```

2. Navigate to the repository directory:

```bash

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](https://scikit-learn.org/): The scikit-learn library for machine learning in Python.

- [NumPy](https://numpy.org/): The NumPy library for numerical computing in Python.

- [pandas](https://pandas.pydata.org/): The pandas library for data manipulation and analysis in Python.