Pattern recognition demo

This is a simple demo of binary classification, in which the machine tries to recognize patterns drawn by hand. It shows how one can build a training set by labeling examples and then make predictions for pictures of unknown patterns.

This demo implements two classifiers: $K$-nearest neighbors and the perceptron.

Build a training set

Start by drawing a pattern and .
Then, draw a different pattern and .
Do this multiple times to collect a sample of drawings (of these 2 different patterns).

Make predictions

When you have enough data, draw a new example and ask the machine to or .

At any time, you can or

Training set: