A framework for user assistance on predictive models

Abstract

International audienceData analysis generally requires very specialized skills, especiallywhen applying machine learning tasks. The ambition of the paperis to propose a framework assisting a domain expert user to analysehis data, in a context of predictive analysis. In particular, the frame-work includes a recommender system for the workflow of analysistasks. Because the lack of explanation in recommendations can leadto loss of confidence, a complementary system is proposed to betterunderstand the predictive models recommended. This complemen-tary system aims to help the user to understand and exploit theresults of the data analysis, by relying on his data expertise. Theframework is validated through a pool of questions and a mock-upshowing the interest of the approach