ksdkamesh99/KNN-Visualiser
It is a best Visualiser for implementing K-Nearest Neighbours Algorithm with 3 different classes i.e A,B,C. It is developed using ml5.js and p5.js.
This tool helps you understand how the K-Nearest Neighbors (KNN) classification algorithm works by visually demonstrating its predictions. You input training data points belonging to three distinct categories (A, B, or C) by clicking on a canvas. The output is a clear visualization of how new, unlabeled points are classified into one of these categories based on their proximity to the training data. This is ideal for students or educators learning about machine learning concepts.
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Use this if you are an educator or student who wants a simple, interactive way to visualize and understand the K-Nearest Neighbors algorithm without needing to write code.
Not ideal if you need to apply KNN to real-world datasets, evaluate its performance with metrics, or customize the algorithm's parameters beyond basic visualization.
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Language
HTML
License
MIT
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Last pushed
Jan 10, 2021
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