Machine Learning
It’s Time to Consider “Time” when Evaluating Recommender-System Algorithms (Peprint)
We published a preprint on arXiv, in which we question the current practice of calculating evaluation metrics for recommender systems as single numbers (e.g. precision p=.28 or mean absolute error MAE = 1.21). We argue that single numbers express only average effectiveness over usually a rather long period (e.g. a Read more…