Journal of Chemistry and Chemical Research

In the weathering process of ancient glass, due to a large amount of exchange between internal elements and environmental elements, the composition proportion of ancient glass changed, which affected the correct judgment of its category. This paper conducts relevant classification research and judgment through statistical analysis of known data, and uses K-means++algorithm without supervision to analyze and identify the composition of glass products. First, conduct data preprocessing, delete the two wrong data numbered 15 and 17 according to the requirements of the title, set the part with blank color as black according to the weathering degree law, fill in "0" for other blank values, and conduct the next calculation. First, use chi square test to analyze the four categorical variables, According to whether the significance P value is less than 0.05, it can be judged that there is a significant difference between glass type and color and surface weathering, and there is no significant difference between glass type and color and ornamentation. On this basis, quantitative analysis of effects is conducted, including phi, Crammers V, contingency coefficient and lambda

glass composition identification; Chi square test; Weighted average forecast; System clustering; K-Means