Principles of Numerical Taxonomy¶
Sokal, R. R., & Sneath, P. H. A. (1963). Principles of Numerical Taxonomy.
Cited by¶
1 citation across 1 artifact.
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Primes¶
- Classification
- Classification is foundational across biology (Linnaean taxonomy), medicine (nosology and ICD coding), machine learning (supervised learning), library science (subject hierarchies), and law (offense categories and procedural rules), and in each domain it solves the same core problem: how to reduce infinite variation into finite, manageable categories that preserve relevant distinctions, as Sokal and Sneath (1963) systematized in their foundational work on numerical taxonomy.
This sourceW. H. Freeman. Foundational treatment establishing classification as a general, quantitative methodology that reduces variation to manageable categories preserving relevant distinctions, applicable across biology, medicine, and beyond.
- Classification is foundational across biology (Linnaean taxonomy), medicine (nosology and ICD coding), machine learning (supervised learning), library science (subject hierarchies), and law (offense categories and procedural rules), and in each domain it solves the same core problem: how to reduce infinite variation into finite, manageable categories that preserve relevant distinctions, as Sokal and Sneath (1963) systematized in their foundational work on numerical taxonomy.
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