Mushroom Classification

Overview and Purpose

This project started as an introductory exploration into Kedro.

More bluntly put, it started as a search to better organize machine learning pipelines

Dataset Context

Link to Dataset on UCI ML Website

• Mushrooms do not have a simple heuristic for understanding if a species is poisonous
• The machine learning pipelines seek to first create a standard binary classifier for determing if mushrooms are poisonous
• Then, additional functions are used to create a simpler tree-based classifier from the most important features
• The tree-based method is later outputted to an image for future reference

How to get started

1. clone repository with:

git clone https://github.com/van-william/kedro-classification-mushrooms.git

2. Install dependencies with:

pip install -r src/requirements.txt

3. Run pipelines in command line:

kedro run

NOTE: the above command runs the default pipeline(s); in this case, it runs data processing then exploratory data analysis then data science. All three pipelines can be run individually with the below commands:

kedro run --pipeline dp
kedro run --pipeline eda
kedro run --pipeline ds

Notebook Usage

• A Jupyter Notebook was used for initial EDA, scratchwork
• This is provided in the Notebooks directory

Example Output

See below for an example image output of a simplified heuristic for mushroom poison test (~99% accurate for 23 varieties)