k-Nearest Neighbor Classifier

First try with one of the simplest classifier: The k-Nearest Neighbor Classifier...




This post is inspired by the video of Josh Gordon (below) about the Python implementation of a k-NN classifier. Watch this video to understand the principle and after that let's see how to do the same thing in JavaScript/ImageJ.

1. The data

Just to remind you the image of Fig. 1 which is composed of three different shapes: (i) circles, (ii) squares, and (iii) triangles of various sizes and orientations. Here, we would like to count their numbers.

Fig.1: Image of squares, circles, and triangles.

Several features were calculated from this image thanks to ImageJ and saved as a CSV file.

4. Our implementation

In the video, the kNN classifier is based on two main functions:

• fit(x_train,y_train) returning an object containing the "model".
• predict(x_test) returning an array of numbers (the predictions).
• closest(self,x) is an auxiliary function used by the function predict(..).

Here is the skeleton of the implementation of the kNN classifier

TODO

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5. Other crazybiocomputing posts

Further readings are available in ...

• Machine Learning Glossary
• Programming in JavaScript Series  [Link]
• JavaScript/ECMAScript TOC [Link]