Help Understanding Cross Validation and Decision Trees

Question

I\'ve been reading up on Decision Trees and Cross Validation, and I understand both concepts. However, I\'m having trouble understanding Cross Validation as it pertains to D

Answer 1

It has been mentioned already that the purpose of the cross-validation is to qualify the model. In other words cross-validation provide us with an error/accuracy estimation of model generated with the selected "parameters" regardless of the used data. The corss-validation process can be repeated using deferent parameters untill we are satisfied with the performance. Then we can train the model with the best parameters on the whole data.