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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 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 ).
Learning that takes place in varying contexts can create more links and encourage generalization of the skill or knowledge. [3] Connections between past learning and new learning can provide a context or framework for the new information, helping students to determine sense and meaning, and encouraging retention of the new information.
Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. [1] The ability to learn is possessed by humans, non-human animals, and some machines; there is also evidence for some kind of learning in certain plants. [2]
Operant conditioning, also called instrumental conditioning, is a learning process where voluntary behaviors are modified by association with the addition (or removal) of reward or aversive stimuli. The frequency or duration of the behavior may increase through reinforcement or decrease through punishment or extinction .
Download as PDF; Printable version; In other projects ... For supervised learning applications in machine learning and statistical learning theory, generalization ...
The study of stability gained importance in computational learning theory in the 2000s when it was shown to have a connection with generalization. [1] It was shown that for large classes of learning algorithms, notably empirical risk minimization algorithms, certain types of stability ensure good generalization.
In machine learning, lazy learning is a learning method in which generalization of the training data is, in theory, delayed until a query is made to the system, as opposed to eager learning, where the system tries to generalize the training data before receiving queries.