i read your paper and code, is the measures: average precision + average recall + F1 actually the same as the traditional "precision" "recall" "F1" in top-k item recommendation scenario?
i want to run the LEAP baseline to compare with other top-k medicine recommendation method(similar to the traditional top-k item recommendation design). In LEAP and your paper, the prediction medicine length is automatically decided by the model, how should i compare the results between the LEAP kind of models and the fixed top-K length models?
Do you think it is fair to just choose the best top-k results to compare with the LEAP kind of models?
i read your paper and code, is the measures: average precision + average recall + F1 actually the same as the traditional "precision" "recall" "F1" in top-k item recommendation scenario?
i want to run the LEAP baseline to compare with other top-k medicine recommendation method(similar to the traditional top-k item recommendation design). In LEAP and your paper, the prediction medicine length is automatically decided by the model, how should i compare the results between the LEAP kind of models and the fixed top-K length models? Do you think it is fair to just choose the best top-k results to compare with the LEAP kind of models?
Wait for your response and thank you!