Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

11

ICPR
2008
IEEE

favoriteEmaildiscussreport

136views Computer Vision» more ICPR 2008»

Generalized Chebyshev Kernels for Support Vector Classification

13 years 11 months ago

Generalized Chebyshev Kernels for Support Vector Classification

Download figment.cse.usf.edu

In this paper, a method to generalize previously proposed Chebyshev Kernel function is presented for Support Vector Classification in order to obtain more robust and higher classification accuracy. By introducing the generalized Chebyshev polynomials for vector inputs, we increase the performance of this kernel function. The simulation results show that the proposed generalized Chebyshev Kernel has better performance than the previously proposed kernel for Support Vector Classification. Early simulation results show that the proposed kernel function yields the best classification results for a Breast Cancer dataset.

Sedat Ozer, Chi Hau Chen

Real-time Traffic

Chebyshev Kernel | Chebyshev Kernel Function | Computer Vision | ICPR 2008 | Kernel Function |

claim paper

Related Content

» Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues

» Support vector machine for functional data classification

» Evolving kernels for support vector machine classification

» Kernel Logistic Regression and the Import Vector Machine

» Generalized Discriminant Analysis Using a Kernel Approach

» Training of Support Vector Machines with Mahalanobis Kernels

» Support Vector Machine Classification with Indefinite Kernels

» Cryptographically private support vector machines

» Gene Selection for Tumor Classification Using Microarray Gene Expression Data

Post Info
More Details (n/a)

Added	30 May 2010
Updated	30 May 2010
Type	Conference
Year	2008
Where	ICPR
Authors	Sedat Ozer, Chi Hau Chen

Comments (0)