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A Guide to Similarity Measures
- Publication Year :
- 2024
-
Abstract
- Similarity measures play a central role in various data science application domains for a wide assortment of tasks. This guide describes a comprehensive set of prevalent similarity measures to serve both non-experts and professional. Non-experts that wish to understand the motivation for a measure as well as how to use it may find a friendly and detailed exposition of the formulas of the measures, whereas experts may find a glance to the principles of designing similarity measures and ideas for a better way to measure similarity for their desired task in a given application domain.<br />Comment: 27 pages
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2408.07706
- Document Type :
- Working Paper