Measuring technical efficiency for multi-input multi-output production processes through OneClass Support Vector Machines: a finite-sample study

Multi-output least-squares support vector regression machines

a Information Technology Supporting Center, Institute of Scientific and Technical Information of China No. 15 Fuxing Rd., Haidian District, Beijing 100038, China b School of Economics and Management, Beijing Forestry University No. 35 Qinghua East Rd., Haidian District, Beijing 100038, China College of Information and Electrical Engineering, China Agricultural University No. 17 Qinghua East Rd....

A multi-class extension for multi-labeler support vector machines

In recent years, there has been an increasing interest in the design of pattern recognition systems able to deal with labels coming from multiple sources. To avoid bias during the learning process, in some applications it is strongly recommended to learn from a set of panelists or experts instead of only one. In particular, two aspects are of interest, namely: discriminating between confident a...

Multi-Layer Support Vector Machines

1.

Multi-prototype Support Vector Machines

We extend multiclass SVM to multiple prototypes per class. This allows to combine several simple models (e.g. linear models) in a principled way to get much more expressive decision functions. For this framework, we give a compact constrained quadratic formulation and we suggest an ef£cient algorithm for its optimization that guarantees a local minimum of the objective function. An annealed pro...

Multi-class Support Vector Machines