1. A computer-implemented method comprising: obtaining, for a sequence of strokes that represent a handwritten input, cut point data indicating one or more particular candidate cut points that are identified within the sequence of strokes; obtaining, for the one or more of the particular candidate cut points, feature data indicating one or more features of the particular candidate cut point; for each of the one or more particular candidate cut points, providing the feature data to a classifier that is trained to predict, based on one or more features of a candidate cut point, a likelihood of the candidate cut point being a correct cut point; for each of the one or more particular candidate cut points, receiving, from the classifier, data indicating the likelihood that the particular candidate cut point is a correct cut point; selecting a set of one or more of the particular candidate cut points whose respective likelihoods satisfy a threshold; and using the set of candidate cut points to segment the sequence of strokes.