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Dynamic model: Difference between revisions
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{{see also|Machine learning terms}} | {{see also|Machine learning terms}} | ||
==Introduction== | ==Introduction== | ||
A [[dynamic model]] in [[machine learning]] refers to a type of [[model]] that can adjust its behavior over time in response to changes in its environment or new information. The dynamic model is frequently or even continuously [[retrained]]. It is | A [[dynamic model]] in [[machine learning]] refers to a type of [[model]] that can adjust its behavior over time in response to changes in its environment or new information. The dynamic model is frequently or even continuously [[retrained]]. It is also known as an '''online model'''. Dynamic models are especially beneficial in situations where the environment or data being used to train a model is constantly shifting. | ||
The opposite of the dynamic model is [[static model]]. | The opposite of the dynamic model is [[static model]]. | ||