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Orientador(es)
Resumo(s)
This work was conducted in the context of industrial mathematics, in partnership with CTT-Correios de Portugal, S.A., highlighting the strong link between academia and the business world. It addresses the classification of Postal Distribution Centres using multivariate statistical methods combined in a less common way. First, a correlation analysis was conducted on the variables selected for the study, revealing several statistically significant associations. To mitigate collinearity, Principal Component Analysis was applied to derive uncorrelated components, which were then used as inputs to Cluster Analysis. Both hierarchical and partitional clustering methods were applied, and solution quality was assessed using graphical inspection, silhouette coefficients, and within- and between-cluster sums of squares. Ward’s method, k-means, and k-medoids produced consistent and similar groupings; in this paper, the k-means results are considered. Linear Discriminant Analysis and Multinomial Logistic Regression were used to assign new Postal Distribution Centres to the previously identified groups. The second classifier was used to corroborate the classification results obtained by LDA, since some LDA assumptions are violated and one of the clusters is small. The classification results from both methods showed a high degree of agreement. To avoid inflated accuracy caused by using the same data throughout all stages of the pipeline (standardisation, PCA, CA, LDA/MLR), the leave-one-out cross-validation method was applied across the entire pipeline, rather than only at the classification stage. As a result, the accuracy value obtained is a more realistic estimate of the model’s performance. All analyses were conducted in R.
Descrição
Palavras-chave
Industrial mathematics Postal distribution centres Principal component analysis Cluster analysis Linear discriminant analysis Multinomial logistic regression Cross-validation
Contexto Educativo
Citação
Aleixo, S. M., Fernandes, C., Ramos, P., Ramires, M., & Milho, R. (2027). Classification of postal distribution centres. In O. Gervasi et al. (Eds.), Computational science and its applications – ICCSA 2026 workshops (Lecture Notes in Computer Science, Vol. 16759). Springer. https://doi.org/10.1007/978-3-032-30518-3_15
Editora
Springer
Coleções
Licença CC
Sem licença CC