K-Nearest Neighbors (KNN)

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🎯 Time to Practice!

Now that you understand the KNN algorithm, interact with the visualization below to experiment with different distance metrics (Euclidean, Manhattan, Minkowski, Cosine), adjust the K value, and drag the query point to see how nearest neighbors are identified!

Explore how KNN predicts outcomes by visualizing distance metrics like Euclidean and Manhattan to identify the closest neighbors in a dataset.

Note: The black dot represents the query point. Drag it to any position on the canvas to explore how the nearest neighbors change.

Select Distance Metric:

K: 3

▼ How to Use This Tool

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Quick Knowledge Check

Test your understanding before moving on

Question 1 of 3