thanks for the answer! it covers the follow-up question to the first commentator. Just one last question in your example what is the rule of thump to avoid very few variables and too much? like is there an accepted level of accuracy?

So if I gave it the 100 pics without stopping criteria and then tested it on a much larger data set, say, 1000 pics, will the detection error increase or is this not considered overfitting since it trained on a dataset and then used on a completely different set?