Classification Using Geometric Level Sets

Classification using geometric level sets Citation

A variational level set method is developed for the supervised classification problem. Nonlinear classifier decision boundaries are obtained by minimizing an energy functional that is composed of an empirical risk term with a margin-based loss and a geometric regularization term new to machine learning: the surface area of the decision boundary. This geometric level set classifier is analyzed i...

Using DEA to compute most favourable and least favourable sets of weights in ABC inventory classification

Detection of some Tree Species from Terrestrial Laser Scanner Point Cloud Data Using Support-vector Machine and Nearest Neighborhood Algorithms

acquisition field reference data using conventional methods due to limited and time-consuming data from a single tree in recent years, to generate reference data for forest studies using terrestrial laser scanner data, aerial laser scanner data, radar and Optics has become commonplace, and complete, accurate 3D data from a single tree or reference trees can be recorded. The detection and identi...

Classification and properties of acyclic discrete phase-type distributions based on geometric and shifted geometric distributions

Acyclic phase-type distributions form a versatile model, serving as approximations to many probability distributions in various circumstances. They exhibit special properties and characteristics that usually make their applications attractive. Compared to acyclic continuous phase-type (ACPH) distributions, acyclic discrete phase-type (ADPH) distributions and their subclasses (ADPH family) have ...

A geometric measure-type regularity criterion for solutions to the 3D Navier–Stokes equations

A local anisotropic geometric measure-type condition on the super-level sets of solutions to the 3D NSE preventing the formation of a finite-time singularity is presented; essentially, local one-dimensional sparseness of the regions of intense fluid activity in a very weak sense. Mathematics Subject Classification: 35,76