The non-Edible Mushroom Kingdom is my analysis and findings on UCI Machine Learning Mushroom Classification dataset and machine learning models that would best predict whether a mushroom is edible or poisonous. The various models I trained on this dataset were decision trees (entropy and gini index), random forest (entropy and gini index), and naive Bayes. Utilized k-fold cross-validation to estimate the generalization of each model on a limited subset of the training data and graphviz to visualize various models to identify key features that help each model predict whether a mushroom is poisonous and edible.
These instructions will give you a copy of the neural network up and running on your local machine for development and testing purposes.
To run this application locally on your computer, you'll need Git, Python, and Jupyter Notebook or any platform that will be able to run .ipynb files installed on your computer.
Then run the following command in the command line and go to the desired directory to store this project:
Clone this repository:
git clone https://github.com/JonathanCen/The-non-Edible-Mushroom-Kingdom.git
Open Jupyter Notebook or equivalent.
Navigate to the cloned repository.
Start running and editing the notebook!
- Jupyter Notebook - For creating and sharing computational documents
All issues and feature requests are welcome. Feel free to check the issues page if you want to contribute.
Copyright © 2022 Jonathan Cen.
This project is MIT licensed.