What is k-value optimization in machine learning?

What is k-value optimization in machine learning?

K-value optimization refers to selecting the best 'k' value in algorithms like K-Nearest Neighbors to improve accuracy.

How do I determine the optimal k value for my model?

You can use techniques like cross-validation, the elbow method, or grid search to find the optimal k value.

What happens if I choose a k value that is too low?

A low k value can lead to overfitting, where the model captures noise in the data rather than the underlying pattern.

And what if the k value is too high?

A high k value can lead to underfitting, where the model becomes too generalized and misses important patterns.