Model parameter - Revision history

Vipul at 16:31, 7 June 2014

2014-06-07T16:31:04Z

← Older revision		Revision as of 16:31, 7 June 2014
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	==Definition==		==Definition==

	In machine learning, the term '''parameter''' is used for initially unknown numerical values that are part of a general functional form used to predict outputs from inputs. For a specific choice of the value of each parameter, we get a specific function that predicts outputs from inputs. The goal of machine learning problems is to determine a good choice of the set of parameter values to be able to predict the outputs well from the inputs.		In machine learning, the term '''model parameter''' or '''parameter''' is used for initially unknown numerical values that are part of a general functional form used to predict outputs from inputs. For a specific choice of the value of each parameter, we get a specific function that predicts outputs from inputs. The goal of machine learning problems is to determine a good choice of the set of parameter values to be able to predict the outputs well from the inputs.

	==Related notions==		==Related notions==

	* [[~~Hyperparameter~~]] is a ~~constant~~ that ~~controls the [[learning algorithm]] itself. The choice of hyperparameter affects how quickly the algorithm finds the parameters, and might also affect the~~ choices of ~~parameter values themselves~~.		* [[Model hyperparameter]] is used for a (typically discrete) parameter that selects between different choices of model.

Vipul: Vipul moved page Parameter to Model parameter

2014-06-07T16:28:26Z

Vipul moved page Parameter to Model parameter

← Older revision	Revision as of 16:28, 7 June 2014
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Vipul: Created page with "==Definition== In machine learning, the term '''parameter''' is used for initially unknown numerical values that are part of a general functional form used to predict outputs..."

2014-06-07T15:00:32Z

Created page with "==Definition== In machine learning, the term '''parameter''' is used for initially unknown numerical values that are part of a general functional form used to predict outputs..."

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==Definition==

In machine learning, the term '''parameter''' is used for initially unknown numerical values that are part of a general functional form used to predict outputs from inputs. For a specific choice of the value of each parameter, we get a specific function that predicts outputs from inputs. The goal of machine learning problems is to determine a good choice of the set of parameter values to be able to predict the outputs well from the inputs.

==Related notions==

* [[Hyperparameter]] is a constant that controls the [[learning algorithm]] itself. The choice of hyperparameter affects how quickly the algorithm finds the parameters, and might also affect the choices of parameter values themselves.