To recognize and categorize different mouse gestures using simple logistic regression. The model is trained with very high accuracy (98%). I had some doubt about overfitting too but it works very well in practice.

1. U (letter u): U
2. Alpha (greek alpha letter): α. Unfortunately, the way I write alpha makes it looks like the Ichthys symbol.
3. Hat: ^
4. Z (letter z): Z
5. The derivative symbol (looks like an intverted 6): ∂
6. Triangle (equilateral triangle pointing upward): △
7. Greater than: >

This list is definitely extendable simply by adding more training samples and let the model learn them.

To start the demo, start the http server first by running

$python server.py

Then you can run the demo jar

$java -jar Demo.jar

The demo will exit after 20s. To run it for a long while, use the following (Ctrl + C twice to exit)

while true ; do java -jar Demo.jar ; done

Register the drawing by holding down left ctrl, draw a pattern with the mouse, and release left ctrl. The server will try to recognize the pattern and a small popup will appear if a symbol is recognized.

1. JNativeHook (for the demo only)
2. scikitlearn
3. Argo JSON