Question

I was wondering what happens when an image not in the training set is provided to the model in a multiclassification problem? Does it just classify something which is close to this image?

Was it helpful?

Solution

As the model is not trained to recognize an image from this new specific class, the only thing it will do, is to give a probability-or similarity measure for each of the classes for which the model has been trained on. Hence in a Classification problem, the class with the highest probability for this testing image will be the classification output.

Licensed under: CC-BY-SA with attribution
Not affiliated with datascience.stackexchange
scroll top