You implemented the KNN algorithm, and the model is performing poorly. What are the parameters you would tune, and how would you approach choosing the optimal K and distance metric?
- Increase K and use Euclidean distance
- Reduce dimensions and use any distance metric
- Use cross-validation to find optimal K and distance metric
- Use the same K for all datasets
Utilizing cross-validation helps in finding the optimal value of K and selecting an appropriate distance metric, leading to improved performance in KNN.
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