Add Measure - Revision history

Dgorissen at 18:57, 29 September 2009

2009-09-29T18:57:13Z

← Older revision		Revision as of 18:57, 29 September 2009
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	In order for a modeling algorithm to work some kind of [[Measures\|measure]] is needed that scores models and guides the search towards a good local optimum. A model can be scored in many different ways: using a separate validation set, simply the error in the fitted samples, cross validation, minimum description length (MDL), etc.		Before starting ensure you are familiar with [[OO_Programming_in_Matlab]].


			In order for a [[Add_Modeling_Algorithm \| modeling algorithm]] to work some kind of [[Measures\|measure]] is needed that scores models and guides the search towards a good local optimum of the model parameter space (NOT of the simulator!!). A model can be scored in many different ways: using a separate validation set, simply the error in the fitted samples, cross validation, minimum description length (MDL), etc.

	You are free to implement your own [[Measures\|measures]] and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.		You are free to implement your own [[Measures\|measures]] and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.
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	* Go to the src/matlab/measures subdirectory and take a look at the most simple measure: SampleError		* Go to the src/matlab/measures subdirectory and take a look at the most simple measure: SampleError
	* Make a copy of the SampleError directory and give it the same of your Measure		* Make a copy of the SampleError directory and give it the same of your Measure
	* ~~There are~~ two methods ~~you should provide~~:		* You should subclass Measure and ensure two methods are provided:
	** a constructor to read out the configuration information (if any) and construct the object		** a constructor to read out the configuration information (if any) and construct the object
	** a calculateMeasure method that, given a model, returns a positive score where a lower score indicates a better model		** a calculateMeasure method that, given a model, returns a positive score where a lower score indicates a better model

	~~Before starting ensure you are familiar with [[OO_Programming_in_Matlab]].~~

Dgorissen at 15:05, 26 March 2009

2009-03-26T15:05:38Z

← Older revision		Revision as of 15:05, 26 March 2009
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	You are free to implement your own [[Measures\|measures]] and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.		You are free to implement your own [[Measures\|measures]] and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.

	~~Implementing~~ a new measure ~~requires~~ the following ~~(see~~ src/matlab~~/modelbuilders~~/measures):		To implement a new measure we suggest the following:
	* a constructor to read out the configuration ~~objects~~
	* a calculateMeasure method that, given a model, returns a positive score where a lower score indicates a better model		* Go to the src/matlab/measures subdirectory and take a look at the most simple measure: SampleError
			* Make a copy of the SampleError directory and give it the same of your Measure
			* There are two methods you should provide:
			** a constructor to read out the configuration information (if any) and construct the object
			** a calculateMeasure method that, given a model, returns a positive score where a lower score indicates a better model

			Before starting ensure you are familiar with [[OO_Programming_in_Matlab]].

Admin at 16:19, 8 February 2009

2009-02-08T16:19:44Z

← Older revision		Revision as of 16:19, 8 February 2009
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	In order for a modeling algorithm to work some kind of measure is needed that scores models and guides the search towards a good local optimum. A model can be scored in many different ways: using a separate validation set, simply the error in the fitted samples, cross validation, minimum description length (MDL), etc.		In order for a modeling algorithm to work some kind of [[Measures\|measure]] is needed that scores models and guides the search towards a good local optimum. A model can be scored in many different ways: using a separate validation set, simply the error in the fitted samples, cross validation, minimum description length (MDL), etc.

	You are free to implement your own measures and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.		You are free to implement your own [[Measures\|measures]] and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.

	Implementing a new measure requires the following (see src/matlab/modelbuilders/measures):		Implementing a new measure requires the following (see src/matlab/modelbuilders/measures):
	* a constructor to read out the configuration objects		* a constructor to read out the configuration objects
	* a calculateMeasure method that, given a model, returns a positive score.		* a calculateMeasure method that, given a model, returns a positive score where a lower score indicates a better model

Dgorissen at 14:49, 10 May 2007

2007-05-10T14:49:37Z

New page

In order for a modeling algorithm to work some kind of measure is needed that scores models and guides the search towards a good local optimum. A model can be scored in many different ways: using a separate validation set, simply the error in the fitted samples, cross validation, minimum description length (MDL), etc.

You are free to implement your own measures and add them to the toolbox. For example, this could be useful if you want to enforce a problem specific property. Say you are modeling a passive electronic component and you want to ensure the model retains passivity. This can be done by implementing a custom measure that performs the necessary checks.

Implementing a new measure requires the following (see src/matlab/modelbuilders/measures):
* a constructor to read out the configuration objects
* a calculateMeasure method that, given a model, returns a positive score.