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