Support vector machine-based method for analysis of spectral data
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United States of America Patent
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Jun 11, 2013
Grant Date -
Aug 12, 2010
app pub date -
Feb 4, 2010
filing date -
Aug 7, 2000
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Abstract
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 pre-processed 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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