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- W1973746459 abstract "Kernel based methods and Support Vector Machines (SVMs)cite{Vapnik1998,Smola1998} in particular are a class of learning methods that can be used for non-linear regression estimation. They have often achieved state of the art performance in many areas where they have been applied. The class of functions they choose from is determined by a kernel function. The form of this function is of central importance to kernel based methods. In this topic, I will give a simple description about the core concept of kernel-based methods and SVM and some fresh ideas for creating new kernels with multiscale and interpretability characterizations.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only." @default.
- W1973746459 created "2016-06-24" @default.
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- W1973746459 date "2001-09-21" @default.
- W1973746459 modified "2023-09-23" @default.
- W1973746459 title "<title>Kernel method in pattern recognition and classification</title>" @default.
- W1973746459 doi "https://doi.org/10.1117/12.441450" @default.
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