Composition analysis of ancient glass products based on logistic regression and principal component analysis

In order to analyze and study the composition of ancient glass products, this paper preprocessed the data and carried out statistical analysis of charts to qualitatively analyze the relationship between weathering and color, type and pattern of cultural relics, and established a Logistic regression model for quantitative analysis. There are four types of cultural relics according to the type of cultural relics and whether they are weathered. Through the evaluation model of principal component analysis, the statistical law of weathering and chemical composition content of excavated glass cultural relics is calculated according to the corresponding comprehensive score range of each kind. A multiple linear regression model was established to predict the pre-weathering component content. The correlation and difference between the chemical components of different kinds of glass relics were analyzed. The correlation coefficients of high potassium glass and lead barium glass were analyzed respectively, and the correlation coefficient heat maps were drawn. Determine the relationship between the chemical components and the differences between different chemical components.