Jun ware is one of the famous Chinese ancient porcelain produced in Song dynasty. In this work, support vector machines, as new chemometrics algorithms especially suitable for the data processing of small sample sets, have been used for the mathematical model-building for Jun glazes. It has been found that compared with PCA or KNN algorithms, support vector machines can give more reliable mathematical models for the identification of ancient Jun ware.
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