Treffer: JKernelMachines: A Simple Framework for Kernel Machines.

Title:
JKernelMachines: A Simple Framework for Kernel Machines.
Authors:
Picard, David1 PICARD@ENSEA.FR, Thome, Nicolas2 NICOLAS.THOME@LIP6.FR, Cord, Matthieu2 MATTHIEU.CORD@LIP6.FR
Source:
Journal of Machine Learning Research. May2013, Vol. 14 Issue 5, p1417-1421. 5p.
Database:
Business Source Premier

Weitere Informationen

JKernelMachines is a Java library for learning with kernels. It is primarily designed to deal with custom kernels that are not easily found in standard libraries, such as kernels on structured data. These types of kernels are often used in computer vision or bioinformatics applications. We provide several kernels leading to state of the art classification performances in computer vision, as well as various kernels on sets. The main focus of the library is to be easily extended with new kernels. Standard SVM optimization algorithms are available, but also more sophisticated learning-based kernel combination methods such as Multiple Kernel Learning (MKL), and a recently published algorithm to learn powered products of similarities (Product Kernel Learning). [ABSTRACT FROM AUTHOR]

Copyright of Journal of Machine Learning Research is the property of Microtome Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)