Difference between revisions of "Adaptive Modeling Mode"
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| − | It is possible to switch | + | It is possible to switch off sample selection and run the toolbox for a fixed set of samples, only optimizing the model parameters. This is what we call running in Adaptive Modeling Mode. |
You can switch off adaptive sample selection if you simply do not specify a <SampleSelector> tag in your configuration file. Just remove it. In this case all the available data will be used and only adaptive modeling will be done. There are two possibilities: | You can switch off adaptive sample selection if you simply do not specify a <SampleSelector> tag in your configuration file. Just remove it. In this case all the available data will be used and only adaptive modeling will be done. There are two possibilities: | ||
Revision as of 13:55, 30 January 2008
It is possible to switch off sample selection and run the toolbox for a fixed set of samples, only optimizing the model parameters. This is what we call running in Adaptive Modeling Mode.
You can switch off adaptive sample selection if you simply do not specify a <SampleSelector> tag in your configuration file. Just remove it. In this case all the available data will be used and only adaptive modeling will be done. There are two possibilities:
- Your simulator is a dataset: the whole dataset will be read in one go
- Your simulator is an executable or Matlab script: only the initial samples will be generated and used for adaptive modeling, no further samples will be selected.
This is useful if you just want to see what the best model is you can get for a fixed dataset in a certain amount of time.
