Aug 2, 2019 · According to the authors, the dissimilarity approach is a good alternative to tackle problems when only few samples are available. In this vein, ...
Abstract: Dissimilarity representation is a very interesting alternative for the traditional feature space representation when addressing large multi-class ...
Aug 2, 2019 · A Generalized Kernel Approach to Dissimilarity-based Classification · Computer Science, Mathematics. J. Mach. Learn. Res. · 2001.
Aug 2, 2019 · Dissimilarity representation is a very interesting alternative for the traditional feature space representation when addressing large ...
People also ask
What is the dissimilarity function?
What is the difference between distance and dissimilarity?
What is the difference between dissimilarity and similarity matrix?
What is the dissimilarity matrix in statistics?
The paper addresses the problem of specifying differential weights for variables in the construction of a measure of dissimilarity. An assessor is required.
A review of approaches to learning of dissimilarity features based on matrix spaces and vectors is found in [10] . The dissimilarity characterizing of topology ...
The dissimilarity between sequences is measured by the distance between the distribution vectors by using either the Euclidean distance or the χ2-distance. The ...
Rating
(2) · $270.00 · In stock
This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using ...
In this paper, we study the design of classifiers, directly based on a given set of dissimilarities between objects using a generalized kernel approach. Kernels ...
We present the first dissimilarity-based random forest-clustering approach. The approach works only with distances, thus appropriate for non-vectorial objects. ...