October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Mechanics of K-NN
K-NN can be implemented in many configurations, but in this chapter we will use the semi-supervised approach, starting from a certain number of already assigned samples, and later guessing the cluster membership using the main criteria.
In the following diagram, we have a breakdown of the algorithm. It can be summarized with the following steps:
Flowchart for the K-NN clustering process
Let's go over all the following involved steps, in a simplified form:
- We place the previously known samples on the data structures.
- We then read the next sample to be classified, and calculate the Euclidean distance from the new sample to ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.