Data di Pubblicazione:
2010
Citazione:
Multi-scale support vector regression / S. Ferrari, F. Bellocchio, V. Piuri, N.A. Borghese - In: The 2010 International joint conference on neural networks (IJCNN) : Barcelona, Spain, 18- 23 July 2010 : [proceedings]Piscataway : Institute of electrical and electronics engineers, 2010. - ISBN 9781424469161. - pp. 1-7 (( convegno IEEE International Joint Conference on Neural Networks (IJCNN) tenutosi a Barcelona nel 2010 [10.1109/IJCNN.2010.5596630].
Abstract:
A multi-kernel Support Vector Machine model, called Hierarchical Support Vector Regression (HSVR), is proposed here. This is a self-organizing (by growing) multiscale version of a Support Vector Regression (SVR) model. It is constituted of hierarchical layers, each containing a standard SVR with Gaussian kernel, at decreasing scales. HSVR have been applied to a noisy synthetic dataset. The results illustrate their power in denoising the original data, obtaining an effective multiscale reconstruction of better quality than that obtained by standard SVR. Furthermore with this approach the well known problem of tuning the SVR parameters is strongly simplified.
Tipologia IRIS:
03 - Contributo in volume
Keywords:
Kernel functions; Support Vector Machine; Support Vector Regression
Elenco autori:
S. Ferrari, F. Bellocchio, V. Piuri, N.A. Borghese
Link alla scheda completa:
Titolo del libro:
The 2010 International joint conference on neural networks (IJCNN) : Barcelona, Spain, 18- 23 July 2010 : [proceedings]