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- W3151934229 abstract "At the core of most data analysis tasks and their formulations is a distance. This choice anchors the meaning and the modeling inherent in the patterns found and the algorithms used. However, there are an enormous number of distances to choose from. We attempt to survey those most common within data analysis. This chapter also provides an overview of the most important properties of distances (e.g., is it a metric?) and how they are related to the dual notion of a similarity. We provide some common modeling dynamics which motivate some of the distances, and overview their direct uses in nearest neighbor approaches and how to algorithmically deal with the challenges that arise." @default.
- W3151934229 created "2021-04-13" @default.
- W3151934229 creator A5017619650 @default.
- W3151934229 date "2021-01-01" @default.
- W3151934229 modified "2023-09-24" @default.
- W3151934229 title "Distances and Nearest Neighbors" @default.
- W3151934229 doi "https://doi.org/10.1007/978-3-030-62341-8_4" @default.
- W3151934229 hasPublicationYear "2021" @default.
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