Abstract
Boxplots are well-known exploratory charts used to extract meaningful information from batches of data at a glance. Their strength lies in their ability to summarize data retaining the key information, which also is a desirable property of symbolic variables. In this paper, boxplots are presented as a new kind of symbolic variable. In addition, two different approaches to measure distances between boxplot variables are proposed. The usefulness of these distances is illustrated by means of a hierarchical clustering of boxplot data.
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Arroyo, J., Maté, C., Roque, A.MS. (2006). Hierarchical Clustering for Boxplot Variables. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_7
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DOI: https://doi.org/10.1007/3-540-34416-0_7
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