公开(公告)号：US20240086763A1

公开(公告)日：2024-03-14

申请号：US17944949

申请日：2022-09-14

Applicant: Oracle International Corporation

Inventor： Jeremy Plassmann ,  Anatoly Yakovlev ,  Sandeep R. Agrawal ,  Ali Moharrer ,  Sanjay Jinturkar ,  Nipun Agarwal

IPC: G06N20/00 ,  G06N5/04

CPC classification number: G06N20/00 ,  G06N5/042

Abstract: Techniques for computing global feature explanations using adaptive sampling are provided. In one technique, first and second samples from an dataset are identified. A first set of feature importance values (FIVs) is generated based on the first sample and a machine-learned model. A second set of FIVs is generated based on the second sample and the model. If a result of a comparison between the first and second FIV sets does not satisfy criteria, then: (i) an aggregated set is generated based on the last two FIV sets; (ii) a new sample that is double the size of a previous sample is identified from the dataset; (iii) a current FIV set is generated based on the new sample and the model; (iv) determine whether a result of a comparison between the current and aggregated FIV sets satisfies criteria; repeating (i)-(iv) until the result of the last comparison satisfies the criteria.