Multi-kernel learning for multivariate performance measures optimization
| Autor: | Jingbin Wang, Jianbing Xiahou, Nian Zhang, Nancy McDonald, Fan Lin |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Multivariate statistics Optimization problem business.industry Pattern recognition 02 engineering and technology Multivariate kernel density estimation 03 medical and health sciences 030104 developmental biology Kernel method Artificial Intelligence Variable kernel density estimation Kernel embedding of distributions Kernel (statistics) Radial basis function kernel 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Software Mathematics |
| Zdroj: | Neural Computing and Applications. 28:2075-2087 |
| ISSN: | 1433-3058 0941-0643 |
| Popis: | In this paper, we investigate the problem of optimizing complex multivariate performance measures to learn classifiers for pattern classification problems. For the first time, the multi-kernel learning is considered to construct a classifier to optimize a given nonlinear and non-smooth multivariate classifier performance measure. We estimate and optimize the upper bound of the given multivariate performance measure, instead of optimizing it directly. Moreover, to solve the problem of kernel function selection and kernel parameter tuning, we proposed to construct an optimal kernel by weighted linear combination of some candidate kernels. The learning of the classifier parameter and the kernel weight are unified in a single objective function considering minimizing the upper bound of the given multivariate performance measure. The objective function is optimized with regard to classifier parameter and kernel weight alternately in an iterative algorithm. The developed algorithm is evaluated on two different pattern classification methods with regard to various multivariate performance measure optimization problems. The experiment results show the proposed algorithm outperforms the competing methods. |
| Databáze: | OpenAIRE |
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