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The following statements describe the KNN method. Determine whether each of the statements is true or false.

1. The KNN method is an example of non-parametric approaches.
[Choose]

2. As K increases, the method becomes more flexible.
[Choose]


Sagot :

Final answer:

KNN method is non-parametric and becomes more flexible as K increases.


Explanation:

True: The KNN method is indeed an example of non-parametric approaches. This means it does not make strict assumptions about the form of the underlying data distribution.

True: As K increases in the KNN method, it does become more flexible. Higher values of K lead to smoother decision boundaries, reducing the impact of noise.


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