I have come across few (Machine learning-classification problem) journal papers mentioned about evaluate accuracy with Top-N approach. Data was show that Top 1 accuracy = 42.5%, and Top-5 accuracy = 72.5% in the same training, testing condition. I wonder how to calculate this percentage of top-1 and top-5?
Can some one show me example and steps to calculate this?
Thanks
Top-1 accuracy is the conventional accuracy: the model answer (the one with highest probability) must be exactly the expected answer.
Top-5 accuracy means that any of your model 5 highest probability answers must match the expected answer.
For instance, let's say you're applying machine learning to object recognition using a neural network. A picture of a cat is shown, and these are the outputs of your neural network:
Using top-1 accuracy, you count this output as wrong, because it predicted a tiger.
Using top-5 accuracy, you count this output as correct, because cat is among the top-5 guesses.