Welcome to Pilz¶
Pilz is a machine learning library that makes classification easy to understand and deploy. Named after the German word for mushroom/fungus - organisms that are neither plant nor animal - Pilz bridges the gap between traditional decision trees and neural networks.
Why Pilz?¶
Traditional machine learning models are often "black boxes" - you put data in, get predictions out, but understanding why is difficult. Pilz changes this by generating readable SQL rules that you can directly deploy to your database.
Key Features¶
| Feature | Description |
|---|---|
| Three-Way Splits | Trees have Left, Neutral, and Right branches for better handling of ambiguous cases |
| SQL Output | Generates actual SQL that runs directly in DuckDB |
| Interpretable | Every decision is a clear rule you can read |
| Multi-Class | Handles any number of classes |
| Feature Magic | Automatic categorization of continuous and categorical features |
Quick Example¶
# Train a model
pilz train --datacard mydata.yaml --trainsettings settings.yaml
# Get predictions as SQL
pilz eval --datacard mydata.yaml --evalsettings settings.yaml
The output includes ROC curves, accuracy metrics, and deployable SQL rules.
What You'll Learn¶
- Getting Started - Install and run your first model in 5 minutes
- Tutorials - Step-by-step guides with real datasets
- Core Concepts - How the algorithm actually works
- Reference - Complete command and settings reference
Ready to Start?¶
Pilz - Making ML decisions transparent and deployable.