LS-SVM

Training LS-SVM Classifier in semi-supervised mode

Classification

The learning process typically assumes some form of a priori knowledge of the contextual problem at hand in the form of examplar data associated with labels. These data, called the training set, are used to design a classifier, the performance of which is measured on a separate dataset, called the testing set. This is supervised learning in which the performance of the classifier on the test set is viewed as an estimate of the true performance of the system (i.e. the performance on the whole space).

Syndicate content
ericssonlogo
inocybelogo
canalogo
cienalogo
Civimetrix Telecom logo
mitacslogo
risq logo
nserclogo
promptlogo
ecolepolytechniquelogo
University of Torontologo
frqntlogo
uqlogo
MDEIE logo
cfilogo
ciraiglogo