Abstract
Many data mining applications require the determination of similar or dissimilar objects, patterns, attributes, and events in the data. In other words, a methodical way of quantifying similarity between data objects is required. Virtually all data mining problems, such as clustering, outlier detection, and classification, require the computation of similarity.
“Love is the power to see similarity in the dissimilar.”—Theodor Adorno
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Notes
- 1.
The distances are affected after dimensions are dropped. However, the transformation itself does not impact distances.
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© 2015 Springer International Publishing Switzerland
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Aggarwal, C. (2015). Similarity and Distances. In: Data Mining. Springer, Cham. https://doi.org/10.1007/978-3-319-14142-8_3
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DOI: https://doi.org/10.1007/978-3-319-14142-8_3
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