Abstract
The aim of this study is to investigate the open problem of classification laws and results. First, a comprehensive research method of quantitative analysis-Bayesian discrimination is used to reasonably and accurately investigate the classification laws of high potassium glass and lead-barium glass, obtaining the Bayesian discriminant for high potassium glass ????1 = 2.909????1 - 0.117????2 + 4.487 ????3 + 2.432????4 + 1.097????5 + 3.352????6 + 3.403????7 + 6.303????8 + 2.669????9 + 0.897????10 + 1.882????11 - 4.543????12 + 5.002????14 - 150.381 with the lead-barium glass Bayesian discriminant ????2 = 2.447????1 - 1.195????2 + 42.807????3 + 2.117????4 + 1.0971.534????5 + 3.221????6 + 3.299????7 + 4.830????8 + 2.513????9 + 1.226????10 + 1.590????11 - 5.628????12 + 3.087????13-111.481. Then, using the clustering process-Bayesian discrimination method, the number of sample clusters was roughly determined using systematic clustering, and the data were categorized in detail using K-Means clustering, resulting in the possibility of classifying each of the high-potassium and lead-barium glasses into Three subclasses were identified, and Bayesian discriminant functions were derived for each subclass, and the data were tested to justify the subclasses.
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