K-Nearest Neighbor Algorithm Visualization is an interactive educational tool for understanding one of the fundamental machine learning algorithms. The K-Nearest Neighbor (KNN) algorithm is a classification method that assigns a data point to a category based on the categories of its nearest neighbors. This visualization helps students see how the algorithm works in real-time.
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Learning Objectives:
• Understand the K-Nearest Neighbor classification algorithm
• Visualize how distance metrics affect classification results
• Explore the impact of different K values on decision boundaries
• Learn basic concepts of supervised machine learning and pattern recognition
Suitable for: Secondary Computing, Computer Science, Mathematics, and Data Science lessons
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