Abstract: Incompatible item pairings may be eliminated or at least reduced when multiple items are presented. A pairwise approach is taken to train a machine learning model to return an incompatibility score for any given pair of items, which indicates a degree of incompatibility between the pair of items. Once trained, the machine learning model may be used to determine an incompatibility score for each unique pairing of items in a set of multiple items. In some embodiments, a graph is generated having nodes that correspond to the multiple items and undirected edges between pairs of the nodes. Scores are generated for each edge of the graph, a minimum spanning tree in the graph is determined, and the items are ranked based at least in part on the minimum spanning tree so that the items can be presented according to the ranking.