Welcome to Irissembly, where cutting-edge machine learning meets low-level programming! This project showcases a decision tree classifier for iris flower classification, implemented entirely in AVR Assembly.
- 🔧 Assembly Language Mastery: Implemented using AVR Assembly, pushing the boundaries of what's possible in low-level programming.
- 🌸 Iris Classification: Classifies iris flowers into Setosa, Versicolor, and Virginica.
- 🌲 Decision Tree Model: Uses a decision tree with
max_depth=3for accurate classification.
Efficient buffer management is crucial for this project. Here's how the buffers are utilized:
| 0-7 | 8-15 | 16-23 | 24-31 |
|---|---|---|---|
| 0 | 0 | 0 | Petal Length Lower |
| 0 | 0 | 0 | Petal Length Higher |
| 0 | 0 | 0 | Petal Width Lower |
| 0 | 0 | Comparison Results | Petal Width Higher |
| 0 | 0 | Comp A Lower | Sepal Length Lower |
| 0 | 0 | Comp A Higher | Sepal Length Higher |
| 0 | 0 | Comp B Lower | |
| 0 | 0 | Comp B Higher | Final Result |
The final classification result is stored at memory address 0x00800101, which can be accessed via gdb using (gdb) x /1x 0x00800101.
Check out the quick demo to see Irissembly in action!
Join us in exploring the fascinating intersection of assembly language and machine learning with Irissembly. Dive into the code and see the magic unfold!
Feel free to explore and contribute. Let's push the boundaries of what's possible together!