Overfitting it's when the model fails to generalize well to the new data. In this example we solved the overfitting by manipulating the
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.
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
- Clone this repository to your local machine:
git clone https://github.com/BaraSedih11/ReducingOverfitting.git
- Navigate to the repository directory:
cd ReducingOverfitting
-
Open and run the Jupyter Notebook
quiz.ipynb
using Jupyter Notebook or JupyterLab. -
Follow along with the code and comments in the notebook to understand how to solve overfitting using Python.
- 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.