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| R2012a Documentation → Model-Based Calibration Toolbox | |
Learn more about Model-Based Calibration Toolbox |
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| R2012a Documentation → Model-Based Calibration Toolbox | |
Learn more about Model-Based Calibration Toolbox |
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| Contents | Index |
R = CreateAlternativeModels(R, modeltemplate, criteria) R = CreateAlternativeModels(R, modellist, criteria R = CreateAlternativeModels(R, LocalModels,LocalCriteria,GlobalModels,GlobalCriteria)
This is a method of all model objects: mbcmodel.hierarchicalresponse, mbcmodel.localresponse and mbcmodel.response.
This is the same as the Build Models function in the Model Browser GUI. A selection of child node models are built. The results depend on where you call this method from. Note that the hierarchical model is automatically constructed when CreateAlternativeModels is called for a local model.
This option makes alternative response feature models for each response feature.
R = CreateAlternativeModels(R, models, criteria)
Models is the list of models. You can use a model template file (.mbm) created in the Model Browser, or a cell array of mbcmodel.model objects.
Criteria is the selection criteria for best model (from the statistics available from AlternativeModelStatistics).
This option makes alternative local models as well as alternative response feature models.
R = CreateAlternativeModels(R, LocalModels,LocalCriteria,GlobalModels,GlobalCriteria)
LocalModels is the list of local models - you must pass in an empty matrix).
LocalCriteria is 'Two-Stage RMSE'.
GlobalModels is the list of global models (from the model template).
GlobalCriteria is the selection criteria for best model.
You construct a model template file (such as 'mymodels.mbm') in the Model Browser. From any response (global or one-stage model) with alternative responses (child nodes), select Model > Make Template. You can save the child node model types of your currently selected modeling node as a model template. Alternatively from any response click Build Models in the toolbar and create a series of alternative response models in the dialog.
mymodels = 'mymodels.mbm';
mlist = {};
load('-mat', mymodels);
critera = 'PRESS RMSE';
CreateAlternativeModels(R, [], 'Two-Stage RMSE', mlist,
criteria);Note that the model template contains the variable mlist.
CreateAlternativeModels( RESPONSE, 'alternative_models.mbm', 'Weighted PRESS' )
creates alternative response feature models based upon the model template file alternative_models.mbt, and chooses the best model based upon each model's Weighted PRESS statistic.
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