I have about 1.000.000 samples in total where 70% were for training and the 30% for test.
The training part was done in batches of 100 samples. To test the model, and calculate the accuracy, I can not load all test samples in memory.
Does make sense to use the same idea of training, batch-by-batch, to evaluate the model? If so, an overall accuracy would be the average of batch accuracy?