Fast explanations of scored observations

Abstract

A system, method, and product provide rapid explanations for the scores determined by a neural network for new observations input into the neural network. The explanations are associated with a table of percentile bins for each of the input variables used to define the observation. The table contains for each input variable a number of percentile bins. Each percentile bin contains an expected score for values of the input variable containing with the percentile bin. The expected score in each percentile bin is determined from historical observation data. Preferably each percentile bin is associated with an explanation that describes the meaning of the value of the input variable falling within the percentile bin. During observation processing, a new observation is scored. The value of each input variable in the new observation is compared with the percentile bins for the input variable in the table. The expected score in the percentile bin that contains the value of the input variable is retrieved, and this is repeated for all input variables in the new observation. The explanation associated with the percentile bin that has an expected score closest to the actual score is retrieved and provided as the explanation of the most significant input variable accounting for score. Other explanations from the next closest expected scores may also be retrieved.