  One of the most fascinating challenges in the context of parton density
function (PDF) is the determination of the best combined PDF uncertainty from
individual PDF sets. Since 2014 multiple methodologies have been developed to
achieve this goal. In this proceedings we first summarize the strategy adopted
by the PDF4LHC15 recommendation and then, we discuss about a new approach to
Monte Carlo PDF compression based on clustering through machine learning
algorithms.
