Authors: | Christmann, Andreas Luebke, Karsten Marin-Galiano, Marcos Rüping, Stefan |
Title: | Determination of hyper-parameters for kernel based classification and regression |
Language (ISO): | en |
Abstract: | We investigate methods to determine appropriate choices of the hyper-parameters for kernel based methods. Support vector classification, kernel logistic regression and support vector regression are considered. Grid search, Nelder-Mead algorithm and pattern search algorithm are used. |
Subject Headings: | convex risk minimization kernel logistic regression statistical machine learning support vector machine support vector regression |
URI: | http://hdl.handle.net/2003/21667 http://dx.doi.org/10.17877/DE290R-14494 |
Issue Date: | 2005-11-07T11:39:49Z |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
tr38-05.pdf | DNB | 491.21 kB | Adobe PDF | View/Open |
This item is protected by original copyright |
Items in Eldorado are protected by copyright, with all rights reserved, unless otherwise indicated.