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      Supervised pattern recognition in food analysis.

      Journal of Chromatography. a
      Food Analysis, methods, Pattern Recognition, Automated

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          Abstract

          Data analysis has become a fundamental task in analytical chemistry due to the great quantity of analytical information provided by modern analytical instruments. Supervised pattern recognition aims to establish a classification model based on experimental data in order to assign unknown samples to a previously defined sample class based on its pattern of measured features. The basis of the supervised pattern recognition techniques mostly used in food analysis are reviewed, making special emphasis on the practical requirements of the measured data and discussing common misconceptions and errors that might arise. Applications of supervised pattern recognition in the field of food chemistry appearing in bibliography in the last two years are also reviewed.

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          Author and article information

          Journal
          17540392
          10.1016/j.chroma.2007.05.024

          Chemistry
          Food Analysis,methods,Pattern Recognition, Automated
          Chemistry
          Food Analysis, methods, Pattern Recognition, Automated

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