Sciweavers

SSPR
2004
Springer

Kernel Methods for Exploratory Pattern Analysis: A Demonstration on Text Data

14 years 4 months ago
Kernel Methods for Exploratory Pattern Analysis: A Demonstration on Text Data
Kernel Methods are a class of algorithms for pattern analysis with a number of convenient features. They can deal in a uniform way with a multitude of data types and can be used to detect many types of relations in data. Importantly for applications, they have a modular structure, in that any kernel function can be used with any kernel-based algorithm. This means that customized solutions can be easily developed from a standard library of kernels and algorithms. This paper demonstrates a case study in which many algorithms and kernels are mixed and matched, for a cross-language text analysis task. All the software is available online.
Tijl De Bie, Nello Cristianini
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where SSPR
Authors Tijl De Bie, Nello Cristianini
Comments (0)