Find error rate of a classifier without having y_test
It's not possible since you don't have a ground truth. If you don't know what the test data is labeled, how do you want to know how often you predicted the correct label? 
I would suggest you split your training data set into a training and a test data set and go from there.
I used a random forest classifier and now I want to see how good my classification was. Maybe even perform a grid search. My test data has no labels, meaning I only have x_train, y_train and x_test. Is there a way to calculate the error rate without having the accuracy?
Thank you in advance!