When we do K-fold cross validation, we are testing how well our model is able to get trained by some data and then predict data it hasn't seen.
I selected 9 fold for training, and 1 fold for validation. Training set would be 8 images, and validation set would be 2 images. I have Trained my model with training set, and computed performance with validation set. I have 10 training sets, 10 validation sets, 10 models, and 10 errors.
now What can I do
Do I need to choose a predictive model after I did k-fold cross-validation?
I have read a lot. But I do not understand what is the next step