We introduce a class of random polytopes which simultaneously generalizes several known constructions.
While being fairly general, these polytopes are also computationally exceptionally benign.
We indicate how these properties can be exploited for classification and clustering tasks in data analysis.
Crucially, our construction lets users smoothly trade off between a tighter description of the data and faster computation.