Mass estimation as a means to address shortcomings of data depth and density

Counting data points in a region is more efficient than calculating the distances of all pairs of points. Utilising this methodology this thesis develops novel data modelling methods with desirable characteristics. When applied in specific machine-learning tasks the proposed methods are shown to improve the task-specific performances compared to existing methods.