Solved – Cross validation and parameter tuning

Question

Can anyone tell me what exactly a cross-validation analysis gives as result?
Is it just the average accuracy or does it give any model with parameters tuned?

Because, I heard somewhere that cross-validation is used for parameter tuning.

Answer 1

Cross-validation gives a measure of out-of-sample accuracy by averaging over several random partitions of the data into training and test samples. It is often used for parameter tuning by doing cross-validation for several (or many) possible values of a parameter and choosing the parameter value that gives the lowest cross-validation average error.

So the process itself doesn't give you a model or parameter estimates, but you can use it to help choose between alternatives.