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Machine Learning K-Nearest Neighbors

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Multiple Choice

What is the main idea behind the K-Nearest Neighbors algorithm?

  1. It classifies data points based on the majority vote of their neighbors.
  2. It finds the closest data point to a new data point and assigns the same label.
  3. It calculates the distance between data points and assigns labels based on the shortest distance.
  4. It uses a decision tree to classify data points.
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