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Cardiac Disease Classification Using a Random Forest Model

Description

This model was trained using a random forest model to predict cardiac disease.

Data

The Kaggle data provided by Manu Siddhartha.

EDA

A pandas-profiling report is available.

Code

The code was created in python using Jupyter notebook.

If you have trouble with GitHub rendering the file, please try here.

Documentation

A final summary outlines the work.

Models

The pickle files can be found here.

Instructions

To run this notebook locally, install Jupyter, download the data set, change the file location to load the code and data, and install all the library dependencies.

Try Anaconda.

Tools

  • Python
  • Jupyter Notebook

Credits

Forest image by Michael Krahn at Unsplash

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Random Forest Classifier of binary cardiac disease risk.

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