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  2. Generalization - Wikipedia

    en.wikipedia.org/wiki/Generalization

    Cartographic generalization is the process of selecting and representing information of a map in a way that adapts to the scale of the display medium of the map. In this way, every map has, to some extent, been generalized to match the criteria of display. This includes small cartographic scale maps, which cannot convey every detail of the real ...

  3. Generalization (learning) - Wikipedia

    en.wikipedia.org/wiki/Generalization_(learning)

    Generalization is the concept that humans, other animals, and artificial neural networks use past learning in present situations of learning if the conditions in the situations are regarded as similar. [1] The learner uses generalized patterns, principles, and other similarities between past experiences and novel experiences to more efficiently ...

  4. Inductive reasoning - Wikipedia

    en.wikipedia.org/wiki/Inductive_reasoning

    Inductive reasoning is any of various methods of reasoning in which broad generalizations or principles are derived from a body of observations. [1] [2] This article is concerned with the inductive reasoning other than deductive reasoning (such as mathematical induction), where the conclusion of a deductive argument is certain given the premises are correct; in contrast, the truth of the ...

  5. Cartographic generalization - Wikipedia

    en.wikipedia.org/wiki/Cartographic_generalization

    Cartographic generalization, or map generalization, includes all changes in a map that are made when one derives a smaller-scale map from a larger-scale map or map data. It is a core part of cartographic design. Whether done manually by a cartographer or by a computer or set of algorithms, generalization seeks to abstract spatial information at ...

  6. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    e. In computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant. [1] In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.

  7. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    List of paradoxes. Outline of public relations – Overview of and topical guide to public relations. Map–territory relation – Relationship between an object and a representation of that object (confusing map with territory, menu with meal) Mathematical fallacy – Certain type of mistaken proof.

  8. External validity - Wikipedia

    en.wikipedia.org/wiki/External_validity

    External validity is the validity of applying the conclusions of a scientific study outside the context of that study. [1] In other words, it is the extent to which the results of a study can generalize or transport to other situations, people, stimuli, and times. [2][3] Generalizability refers to the applicability of a predefined sample to a ...

  9. Universal law of generalization - Wikipedia

    en.wikipedia.org/.../Universal_law_of_generalization

    The universal law of generalization is a theory of cognition stating that the probability of a response to one stimulus being generalized to another is a function of the “distance” between the two stimuli in a psychological space. It was introduced in 1987 by Roger N. Shepard, [1] [2] who began researching mechanisms of generalization while ...