Classifications

Classification is the act of organizing objects, concepts, or data into groups or categories based on shared characteristics or rules. The goal is to simplify complexity, improve communication, and support retrieval, analysis, and decision making. Classifications can be descriptive, explanatory, or prescriptive, and they are often formalized in structured schemes such as taxonomies, ontologies, and thesauri.

Key elements of a classification system include the categories (classes) themselves, the criteria or features used to assign items, a labeling scheme, and the structure that connects categories, commonly a hierarchy or network. Hierarchical classifications use levels of increasing specificity, while non-hierarchical or flat systems place items at the same level without nested relations. Classifications may be rule-based, probabilistic, or data-driven, and they can be exhaustive or limited to a defined scope.

Common domains of classification include biology (taxonomy of organisms), library and information science (classification and indexing), medicine (coding systems like ICD), geography (place names and geocoding), and commerce (product categorization). In data science, classification generally refers to supervised learning tasks that assign items to predefined classes; clustering is a related unsupervised approach.

The process typically involves defining the scope and criteria, developing categories, assigning items, and validating reliability. Classifications must be maintained and revised as new knowledge emerges, and they can be affected by cultural, contextual, or temporal factors.

See also taxonomy, ontology, cataloging.