I am currently writing a paper for uni and stumbled across the following problem:
I want to use the 10 Fold Cross Validation method to validate the results of a logistic regression, but I am unsure when to use methods like the Likelihood Ratio Test and Wald Statistic in order to also validate the function and coefficients.
Since the coefficients are going to be created through Gradient Descent based on the data and Cross Validation leads to different sub-sets of data for testing and training, the coefficients and results of the Likelihood Ratio Test and Wald Statistic should differ.
So would you normally have an individual approach for each of sub sets of the Cross Validation or would you rather build one model in advance and use it on each of the sub sets?
As you see I am having difficulties getting a hang on the relation between Gradient Descent, Cross Validation and the Likelihood Ratio Test/Wald Statistic, if someone could explain it to me I would be very thankful.