In a situation where the data is densely packed in some regions and sparse in others, how would the choice of K and distance metric influence the results, and what would be the best approach?

  • Choose a fixed K and Euclidean distance
  • Choose a large K and any distance metric
  • Choose a small K and ignore distance metric
  • Choose an appropriate K and distance metric, considering data distribution
Considering the data distribution and choosing an appropriate value of K and distance metric can help address the issue of varying data density in KNN.
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