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A Framework for User Assistance on Predictive Models

Data analysis generally requires very specialized skills, especially when applying machine learning tasks. The ambition of the paper is to propose a framework assisting a domain expert user to analyse his data, in a context of predictive analysis. In particular, the framework includes a recommender system for the workflow of analysis tasks. Because the lack of explanation in recommendations can lead to loss of confidence, a complementary system is proposed to better understand the predictive models recommended. This complementary system aims to help the user to understand and exploit the results of the data analysis, by relying on his data expertise. The framework is validated through a pool of questions and a mock-up showing the interest of the approach.