Why is the choice of distance metric significant in the K-Nearest Neighbors (KNN) algorithm?
- It affects clustering efficiency
- It defines the complexity of the model
- It determines the similarity measure
- It influences feature selection
The choice of distance metric in KNN significantly impacts how similarity between instances is measured, affecting the neighbors chosen.
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