From maxi-min margin machine classification to regression
The maxi-min margin machine (M 4 ) algorithm, contrast to the traditional support vector machine (SVM) algorithm, gives a more robust solution and gets better generalization performance. In this paper we extend the M 4 classification algorithm to deal with regression problem, and propose a novel reg...
Gespeichert in:
Hauptverfasser: | , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The maxi-min margin machine (M 4 ) algorithm, contrast to the traditional support vector machine (SVM) algorithm, gives a more robust solution and gets better generalization performance. In this paper we extend the M 4 classification algorithm to deal with regression problem, and propose a novel regression method. This method inherits the characteristics of M 4 such as good robustness and generalization performance. In this paper we discuss the linear and nonlinear case of the proposed method, and experimental results indicate its effectiveness and better robustness and generalization performance compared with the traditional SVR algorithm. |
---|---|
DOI: | 10.1109/MEC.2011.6025952 |