Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)

[WITHDRAWN] A Relevance Vector Machine Based on Gaussian Mixture Kernel

Authors
Mi Tong, Fang Liu, Quan Qi, Wangchen Qin
Corresponding Author
Mi Tong
Available Online March 2018.
DOI
https://doi.org/10.2991/mecae-18.2018.82How to use a DOI?
Keywords
Relevant vector machine; Gaussian mixture kernel; Gaussian mixture model.
Abstract
Relevance vector machine (RVM), a sparse Bayesian kernel method in machine learning, has been well-known for its sparsity and probabilistic predictions. Like other kernel methods, it use the kernel functions to map the input instances into higher dimensional space for problem simplicity. At present, the most widely used kernel function is Radial basis function (RBF). However, the RBF kernel does not consider the distribution information of the training samples which sometimes leads to a poor efficiency especially in semi-supervised learning where partially labeled examples are available. Therefore, in this paper, we propose a relevance vector machine base on Gaussian mixture kernel, which explores the distribution features of samples with a probabilistic density model, the Gaussian mixture model (GMM), and merge it into the training process. Applied to several datasets, the proposed method shows significantly better performance than the traditional RVM algorithm.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
Publication Date
March 2018
ISBN
978-94-6252-493-4
DOI
https://doi.org/10.2991/mecae-18.2018.82How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Mi Tong
AU  - Fang Liu
AU  - Quan Qi
AU  - Wangchen Qin
PY  - 2018/03
DA  - 2018/03
TI  - [WITHDRAWN] A Relevance Vector Machine Based on Gaussian Mixture Kernel
BT  - 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/mecae-18.2018.82
DO  - https://doi.org/10.2991/mecae-18.2018.82
ID  - Tong2018/03
ER  -