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- Loss_function abstract "In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or values of one or more variables onto a real number intuitively representing some "cost" associated with the event. An optimization problem seeks to minimize a loss function. An objective function is either a loss function or its negative (sometimes called a reward function or a utility function), in which case it is to be maximized. In statistics, typically a loss function is used for parameter estimation, and the event in question is some function of the difference between estimated and true values for an instance of data. In the context of economics, for example, this is usually economic cost or regret. In classification, it is the penalty for an incorrect classification of an example. In actuarial science, it is used in an insurance context to model benefits paid over premiums. In optimal control the loss is the penalty for failing to achieve a desired value.".
- Loss_function wikiPageID "442137".
- Loss_function wikiPageRevisionID "603359294".
- Loss_function hasPhotoCollection Loss_function.
- Loss_function subject Category:Decision_theory.
- Loss_function subject Category:Econometrics.
- Loss_function subject Category:Information,_knowledge,_and_uncertainty.
- Loss_function subject Category:Loss_functions.
- Loss_function subject Category:Optimal_decisions.
- Loss_function subject Category:Statistical_theory.
- Loss_function type Abstraction100002137.
- Loss_function type Act100030358.
- Loss_function type Action100037396.
- Loss_function type Choice100161243.
- Loss_function type Decision100162632.
- Loss_function type Event100029378.
- Loss_function type Function113783816.
- Loss_function type LossFunctions.
- Loss_function type MathematicalRelation113783581.
- Loss_function type OptimalDecisions.
- Loss_function type PsychologicalFeature100023100.
- Loss_function type Relation100031921.
- Loss_function type YagoPermanentlyLocatedEntity.
- Loss_function comment "In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or values of one or more variables onto a real number intuitively representing some "cost" associated with the event. An optimization problem seeks to minimize a loss function. An objective function is either a loss function or its negative (sometimes called a reward function or a utility function), in which case it is to be maximized.".
- Loss_function label "Función de pérdida".
- Loss_function label "Loss function".
- Loss_function label "Функция потерь".
- Loss_function sameAs Función_de_pérdida.
- Loss_function sameAs 손실_함수.
- Loss_function sameAs m.028_76.
- Loss_function sameAs Q1036748.
- Loss_function sameAs Q1036748.
- Loss_function sameAs Loss_function.
- Loss_function wasDerivedFrom Loss_function?oldid=603359294.
- Loss_function isPrimaryTopicOf Loss_function.