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Numerical taxonomy is a classification system in biological systematics which deals with the grouping by numerical methods of taxonomic units based on their character states. [1] It aims to create a taxonomy using numeric algorithms like cluster analysis rather than using subjective evaluation of their properties.
Such a number is algebraic and can be expressed as the sum of a rational number and the square root of a rational number. Constructible number: A number representing a length that can be constructed using a compass and straightedge. Constructible numbers form a subfield of the field of algebraic numbers, and include the quadratic surds.
"A base is a natural number B whose powers (B multiplied by itself some number of times) are specially designated within a numerical system." [1]: 38 The term is not equivalent to radix, as it applies to all numerical notation systems (not just positional ones with a radix) and most systems of spoken numbers. [1]
As a system of library classification the DDC is "arranged by discipline, not subject", so a topic like clothing is classed based on its disciplinary treatment (psychological influence of clothing at 155.95, customs associated with clothing at 391, and fashion design of clothing at 746.92) within the conceptual framework. [2]
Phenetics provides numerical methods for examining patterns of variation, allowing researchers to identify discrete groups that can be classified as species. Modern applications of phenetics are common for botany, and some examples can be found in most issues of the journal Systematic Botany.
In a number of countries it is the main classification system for information exchange and is used in all types of libraries: public, school, academic and special libraries. [17] [18] [19] UDC is also used in national bibliographies of around 30 countries. Examples of large databases indexed by UDC include: [20]
A large number of algorithms for classification can be phrased in terms of a linear function that assigns a score to each possible category k by combining the feature vector of an instance with a vector of weights, using a dot product. The predicted category is the one with the highest score.
Statistical classification is a problem studied in machine learning in which the classification is performed on the basis of a classification rule. It is a type of supervised learning, a method of machine learning where the categories are predefined, and is used to categorize new probabilistic observations into said categories. When there are ...