Ontology-based Recommender for Distributed Machine Learning Environment

Domain experts in different areas have a large number of options for approaching their specific data analysis problem. In exploration of large data sets on HPC systems, choosing which method to use, or how to tune the parameters of an algorithm to achieve good results are challenging tasks for data analysts themselves. In this paper, we propose a recommendation module for a distributed machine learning environment aiming at helping the end-users to obtain optimized results for their data analysis / machine learning problem.