Abstract
Based on the research on the rules of the classification of the two kinds of glass as the goal, take glass types as the dependent variable, the chemical composition content is the independent variable, and establish a model of decision tree classification, is based on chemical component content of glass type classification rule, then to analyze the chemical composition of each category, according to the laws of the elbow to calculate the clustering analysis, the optimal class number of k, the K-means clustering algorithm was used to subclassify the glass into K classes and quantify the types. The type was taken as the dependent variable, and the content of each chemical component was taken as the independent variable for decision tree classification. The sub-classification results based on the content of each chemical component and the chemical variables with significant effect on the sub-classification results were obtained. Perturbation was introduced to the chemical variables that had a significant effect on the subclassification results, and the subclassification changes after perturbation were studied to verify the sensitivity of the classification results. The results showed that the accuracy and sensitivity of the model were good.
Publisher
Darcy & Roy Press Co. Ltd.
Reference10 articles.
1. Jin Chenxia, Li Fachao, Ma Shijie, Wang Ying. Sampling scheme-based classification rule mining method using decision Tree in Big Data Environment [J]. Knowledge-based Systems, 2020, 244.
2. Dong Minggang, Liu Ming, Jing Chao. One-against-all-based Hellinger distance decision tree for multiclass imbalanced learning [J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23 (2).
3. Greenberg Michael, Swiler Laura, Lowrie Karen. Jon Helton: Pioneer in Uncertainty and Sensitivity Analysis for the Modeling of Complex Physical Systems [J]. Risk Analysis, 2022, and (2).
4. Andi Nugroho, Harco Leslie Hendric Spits Warnars, Ford Lumban Gaol, Tokuro Matsuo. Trend of Stunting Weight for Infants and Toddlers Using Decision Tree [J]. IAENG International Journal of Applied Mathematics, 2022, 52.0 (1.0).
5. Bai Yongyi, Yao Haishen, Jiang Xuehan, Bian Suyan, Zhou Jinghui, Sun Xingzhi, Hu Gang, Sun Lan, Xie Guotong, He Kunlun. Construction of a Non-Mutually Exclusive Decision Tree for Medication Recommendation of Chronic Heart Failure [J]. The Frontiers in Pharmacology, 2022, 12.