If it was overfitted like discussed before it wouldn't recognice those 1000 pictures, because it wouldn't actually know what a cat is but just know exactly the 100 pictures you first gave it. This is exactly overfitting you are fitting the data into 100 pictures and not into detecting Cats, so any new data that you give doesn't work.
That is why you take 80 pictures from the 100 and test the algorithm with the remaining 20 to make sure it detects cats and doesn't overfit into those 80 pictures
random_web_browser t1_j5xlz98 wrote
Reply to comment by alexander-prince in ELI5: What is Overfitting in machine learning and why is it bad? by alexander-prince
If it was overfitted like discussed before it wouldn't recognice those 1000 pictures, because it wouldn't actually know what a cat is but just know exactly the 100 pictures you first gave it. This is exactly overfitting you are fitting the data into 100 pictures and not into detecting Cats, so any new data that you give doesn't work.
That is why you take 80 pictures from the 100 and test the algorithm with the remaining 20 to make sure it detects cats and doesn't overfit into those 80 pictures