To solve this issue the Uniformity-Completeness JSD (UC-JSD) was designed. Instead of binning the raw distribution NLLs, each of the NLLs is used as it is. Given the three NLL vectors for the sampled, training and validation sets of the same size 𝑁𝐿𝐿𝑆 = {𝑁𝐿𝐿 𝑣𝑎𝑙𝑖𝑑𝑎𝑡𝑖𝑜𝑛 , 𝑁𝐿𝐿 𝑡𝑟𝑎𝑖𝑛𝑖𝑛𝑔 , 𝑁𝐿𝐿 𝑠𝑎𝑚𝑝𝑙𝑒𝑑 } and 𝛼 𝑖 = 1/3, the values in each vector are divided by the total sum, giving a probability distribution with as many values as items in the vector.