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In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects, since such representations facilitate processing and statistical analysis.
Feature-rich describes a software system as having many options and capabilities. One mechanism for introducing feature-rich software to the user is the concept of progressive disclosure , a technique where features are introduced gradually as they become required, to reduce the potential confusion caused by displaying a wealth of features at once.
Linguistic meaning of a word is proposed to arise from contrasts and significant differences with other words. Semantic features enable linguistics to explain how words that share certain features may be members of the same semantic domain. Correspondingly, the contrast in meanings of words is explained by diverging semantic features.
Feature detection includes methods for computing abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. The resulting features will be subsets of the image domain, often in the form of isolated points, continuous curves or connected regions.
A thesaurus (pl.: thesauri or thesauruses), sometimes called a synonym dictionary or dictionary of synonyms, is a reference work which arranges words by their meanings (or in simpler terms, a book where one can find different words with similar meanings to other words), [1] [2] sometimes as a hierarchy of broader and narrower terms, sometimes simply as lists of synonyms and antonyms.
Each word can then be reprocessed into a morphological system to extract a term related to that word. Then, several words can share the same meaning, each one will refer to the same term (like in any language). Multiple words share the same meaning and belong to the same term (have the same information).
A definition is a statement of the meaning of a term (a word, phrase, or other set of symbols). [1] [2] Definitions can be classified into two large categories: intensional definitions (which try to give the sense of a term), and extensional definitions (which try to list the objects that a term describes). [3]
Attributes, characteristics of a feature other than location, often expressed as text or numbers; for example, the population of a city. [19] In geography, the levels of measurement developed by Stanley Smith Stevens (and further extended by others) is a common system for understanding and using attribute data.