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Machine Learning K-Nearest Neighbors
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What is the main idea behind the K-Nearest Neighbors algorithm?
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A
It classifies data points based on the majority vote of their neighbors.
💡 Explanation:
The K-Nearest Neighbors algorithm works by finding the k most similar data points (neighbors) to a new data point and then assigning the label of the majority of these neighbors to the new data point.