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A generalization is a form of abstraction whereby common properties of specific instances are formulated as general concepts or claims. [1] Generalizations posit the existence of a domain or set of elements, as well as one or more common characteristics shared by those elements (thus creating a conceptual model ).
Therefore, generalization is a valuable and integral part of learning and everyday life. Generalization is shown to have implications on the use of the spacing effect in educational settings. [13] In the past, it was thought that the information forgotten between periods of learning when implementing spaced presentation inhibited generalization ...
A faulty generalization is an informal fallacy wherein a conclusion is drawn about all or many instances of a phenomenon on the basis of one or a few instances of that phenomenon. It is similar to a proof by example in mathematics. [1] It is an example of jumping to conclusions. [2]
For many types of algorithms, it has been shown that an algorithm has generalization bounds if it meets certain stability criteria. Specifically, if an algorithm is symmetric (the order of inputs does not affect the result), has bounded loss and meets two stability conditions, it will generalize.
An example comes from the research of Tim Clutton-Brock, who found that the black-and-white colobus, a folivore generalist, needs a home range of only 15 ha. On the other hand, the more specialized red colobus monkey has a home range of 70 ha, which it requires to find patchy shoots, flowers and fruit.
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.
The generalized other is a concept introduced by George Herbert Mead into the social sciences, and used especially in the field of symbolic interactionism.It is the general notion that a person has of the common expectations that others may have about actions and thoughts within a particular society, and thus serves to clarify their relation to the other as a representative member of a shared ...
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression.The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value.