发明名称 |
Kernels and kernel methods for spectral data |
摘要 |
Support vector machines are used to classify data contained within a structured dataset such as a plurality of signals generated by a spectral analyzer. The signals are preprocessed to ensure alignment of peaks across the spectra. Similarity measures are constructed to provide a basis for comparison of pairs of samples of the signal. A support vector machine is trained to discriminate between different classes of the samples. to identify the most predictive features within the spectra. In a preferred embodiment feature selection is performed to reduce the number of features that must be considered.
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申请公布号 |
US2005228591(A1) |
申请公布日期 |
2005.10.13 |
申请号 |
US20020267977 |
申请日期 |
2002.10.09 |
申请人 |
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发明人 |
HUR ASA B.;ELLISSEEFF ANDRE;CHAPELLE OLIVIER;WESTON JASON |
分类号 |
G01N33/48;G01N33/50;G06F19/00;G06K9/62;(IPC1-7):G06F19/00 |
主分类号 |
G01N33/48 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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