Training binary classifier on only one data point ( Theoritical question) Say, I'm training a binary classifier to classify Dog vs Cat. Now, say I train my model only on one imagee ( cat). Now I mirror this cat image that I used to train my model. Now on the mirror image I want to make predciton.
Question : What will my model predict ?
does it predict cat, or will it randomly predict either cat or dog
I think it will predict cat beacuse the parameters have been trained only for cat, so irrespective of any input data, the parameters will support prediction for cat. Am I correct ? is my reasoning correct?
It may predict either a cat or a dog depending on your descriptor for cats and dogs, and on your learning algorithm. This is illustrated on the picture below. If the mirrored cat happens to be on the same side of the separating line as the training cat, then it will be classified as a cat. Otherwise, it will be classified as a dog.