A glass classification model for glass artifacts based on PCA and SVM
DOI:
https://doi.org/10.54097/hset.v42i.7107Keywords:
PCA principal component analysis; SVM support vector machine; Sobol sensitivity analysis.Abstract
The Silk Road was an important channel for trade and commerce between East and West in ancient times, and an important link for cultural exchange between East and West, playing an important role in the development of ancient civilization and history. Glass was one of the important goods carried on the Silk Road in ancient times. In this paper, focus on the problem of component analysis and type identification of ancient glass products. This paper extracted the important factors of the data by PCA principal component analysis, reduced the 14-dimensional data to two dimensions, then built a data point distribution map by visualization, and established a linear classification model based on SVM support vector machine. After that, the model is used to identify the type of samples based on the underlying data. The sensitivity indices of each factor were solved by using Sobol method for the sensitivity analysis of the results.
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