Analysis priority of objects from cross-sectional variance

Abstract

There is disclosed in one example a computing apparatus, including: a processor and a memory; a data store having stored thereon trained models Mand M, wherein model Mincludes a clustering model of proximity and prevalence of a first body of computing objects, and Mincludes a clustering model of proximity and prevalence of a second body of computing object; and instructions encoded within the memory to instruct the processor to: receive an object under analysis; apply a machine learning model to compute a global variance score between the object under analysis and M; apply the machine learning model to compute an enterprise variance score between the object under analysis and M; compute from the global variance score and the enterprise variance score a cross-sectional variance score; and assign the object under analysis an analysis priority according to the cross-sectional variance score.