The term top-1 error rate refers method of benchmarking machine learning models in the ImageNet Large Scale Visual Recognition Competition.

The model is considered to have classified a given image correctly if the target label is the model’s top prediction. This is in contrast to the top-5 error rate where the model only needs to identify the correct label in the model’s top 5 predictions.