How K-Nearest Neighbors Works

How K-Nearest Neighbors Works

Brandon Rohrer via YouTube Direct link

Intro

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1 of 8

Intro

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How K-Nearest Neighbors Works

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  1. 1 Intro
  2. 2 for classification
  3. 3 Choice of k matters
  4. 4 Feature scaling matters
  5. 5 Distance metric matters
  6. 6 K-NN with categorical data
  7. 7 for regression
  8. 8 Expensive to compute with large data sets. Sensitive to feature scaling. Sensitive to distance metric.

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