Uploaded March 2023 | Updated September 2026, 2 weeks ago

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Decision boundaries are a useful way to understand a classifier. They essentially show all the outputs of a machine learning model. I’ll show you how to generate decision boundary plots and how to display them on our chart using JavaScript.

The Course: youtube.com/playlist?list=PLB0Tybl0UNfYe9aJXfWw-Dw_4VnFrqRC4

⭐️HOMEWORK⭐️
Calculate the accuracy of the KNN Classifier for all possible values of K and create a line chart. Conclude what the best value is and generate a high resolution (5000x5000) decision boundary plot for it as well. Share snapshots of these charts on my Discord:
discord.com/invite/gJFcF5XVn9
I’ll showcase the first correct answer in a future video.

⭐️LINKS⭐️

📁 Data
github.com/gniziemazity/drawing-data

💻 Code
tps://github.com/gniziemazity/ml-course
✔️ Use P7 to follow along
✔️ P8 is the code after this lesson


⭐️TIMESTAMPS⭐️
00:00 Introduction
00:47 Porting the Evaluation code to NodeJS
08:30 Generating the Decision Boundary image
11:59 Integrate the Decision Boundary plot with the Chart
14:59 High resolution Decision Boundary images
18:20 Homework (Best K)