Multi-class support vector machines for static security assessment of power system

Multi-class Support Vector Machines

Support Vector Machines for Multi-class Classification

A b s t r a c t : Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of K SVMs can be used to solve a K-class classification problem, such a procedure requires some care. In this paper, the scaling problem of different SVMs is highlighted. Various normalization methods are proposed to cope wi...

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...

An Efficient Hybrid Algorithm For Multi - Class Support Vector Machines

The standard support vector machines (SVM) algorithm is originally designed for two-class classification. it has been applied to solve multi-class classification problems. Several algorithms are developed for solving a multi-class problem by SVM such as one-against-one (OAO), one-against-all (OAA), and directed acyclic graph support vector machines (DAGSVM). In this research, a hybrid algorithm...

Probabilistic support vector machines for multi-class alcohol identification

In this work we address the use of support vector machines in multi-category problems. In our case, the objective is to classify eight different inds of alcohols with just one SnO2 sensor using thermomodulation. The use of support vector machines in the field of sensors signals recognition s beginning to be used due to the ability to generalize in a binary classification problem with a small nu...