Sentence examples for maximum margin hyperplane from inspiring English sources

Consequently, the maximum margin hyperplane fits in a feature space with the help of the nonlinear SVM.

SVM as a discriminative tool maps input cepstral feature vector into high-dimensional space and then separates classes with maximum margin hyperplane.

Their power comes from the combination of the kernel trick and maximum margin hyperplane separation.

Selection of kernel function parameter is also important to define the maximum margin hyperplane.

Unlike the traditional SVM that builds a maximum margin hyperplane in the original high-dimensional space where n ~ 10 – 10, MICA-SVM separates biological samples by constructing the maximum margin hyperplane in the spanned subspace where using the meta-samples.

An SVM solves this difficulty by mapping and converting the input space into a high-dimensional space; after that it finds a linear classification model to classify the input data with a maximum margin hyperplane.

They employed AL for selecting the successive batches and the main selection strategy was based on the maximum margin hyperplanes generated by Support Vector Machines.

That is why SVM classifier is called the maximum-margin hyperplane and this is the most distinguishing characteristic compared to other classification algorithms.

This allows the SVM algorithm to fit the maximum-margin hyperplane in the transformed space.

The parameters of the maximum-margin hyperplane are derived by solving large quadratic programming (QP) optimization problems.

Two-class SVMs use a maximum-margin hyperplane that separates the classes of the input vectors in the feature space.