Component Identification and Prediction of Ancient Glass Products Based on Decision Tree Model and SVM Model

Author:

Chen Jin,Jia Ruoyi,Yan Yaxin

Abstract

The study of the patterns of chemical composition of glass objects is an important research method of classifying ancient glass objects. In this paper , we firstly selected suitable indicators and sought classification boundary lines through a decision tree model to discover the classification pattern of ancient glass and verify its accuracy . Secondly, it was sub-classified and divided by means of hierarchical clustering and k-means mean clustering to realise the work of categorisation of known components . Finally an SVM model was built to obtain a confusion matrix map to achieve the classification prediction of unknown components.

Publisher

Darcy & Roy Press Co. Ltd.

Reference11 articles.

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