NDCG measures a model's ability to rank query results in the order of the highest relevance. Actual relevance scores are usually determined by user interaction. For example, if users tend to click on results ranked high on the list, then the NDCG value will be high. Conversely, if users tend to click on query results that are ranked low on the list, it would mean that the ranking model is doing poorly, and the NDCG value will be low. NDCG values range between 0 and 1 with 1 being the highest. Arize computes NDCG using the standard log2 discount function.