Question: Your data science team wants to use the K-nearest neighbor classification algorithm. Someone on your team wants to use a K of 25. What are the challenges of this approach?

1. Higher K values will produce noisy data.
2. Higher K values lower the bias but increase the variance.
3. Higher K values need a larger training set.
4. Higher K values lower the variance but increase the bias.

Answer: The correct answer of the above question is Option D:Higher K values lower the variance but increase the bias.