Difference between revisions of "Tips"

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* the Matlab neural network implementation is very slow! Try to avoid using crossvalidation but use a validation set instead (see [[FAQ|the FAQ entry]]).
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* If you want to benchmark your computer for Matlab speed simply run "bench" in Matlab.
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* if you use the RBF neural network model type and you get a crash in "newrb" this is an error in the matlab toolbox implementation and not anything we can do about (a workaround is available on [[Contact|request]]).  This should be fixed by Matlab 7.5
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* you can switch off adaptive sample selection if you do not specify a <SampleSelector> tag. See [[Adaptive Modeling Mode]].
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* You can switch off adaptive sample selection if you do not specify a [[Config:SequentialDesign| <SequentialDesign>]] tag. See [[Adaptive Modeling Mode]].
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* If you want to benchmark your computer for Matlab speed simply run "bench" in matlab
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* By default Matlab only allocates about 117MB memory space for the Java Virtual Machine.  If you would like to increase this limit (which you should) please follow the instructions [http://www.mathworks.com/support/solutions/data/1-18I2C.html?solution=1-18I2C here]. See also the general memory instructions [http://www.mathworks.com/support/tech-notes/1100/1106.html here].
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* Remember that the Measure (and error function you use) strongly influence the quality and fit of the surrogate model. If you are unhappy with the final model, try a different [[Measures| Measure]] and/or [[FAQ#How_do_I_change_the_error_function_.28relative_error.2C_RMS.2C_....29.3F| error function]]. See also [[Multi-Objective Modeling]].
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* Remember that the Measure (and error function you use) strongly influence the quality and fit of the surrogate model. If you are unhappy with the final model, try a different Measure and/or error function.
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* If the toolbox is too slow for you can speed it up in different ways. See: [[FAQ#How_can_I_make_the_toolbox_run_faster.3F]].
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* By default Matlab warnings are turned off.  To turn them on, either edit configure.m or type 'warning on' before running 'go'.
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* '''A blog''' covering related research can be found here [http://sumolab.blogspot.com/ http://sumolab.blogspot.com].
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* More information on how to run the SUMO toolbox on a cluster/grid with no Matlab installation can be found [[Running_SUMO_on_UGent_HPC|here]].
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* Some helpful scripts to run SUMO on a SGE (sun grid) cluster is [[Sun_NG1|here]].

Latest revision as of 18:20, 17 March 2014

  • If you want to benchmark your computer for Matlab speed simply run "bench" in Matlab.
  • Remember that the Measure (and error function you use) strongly influence the quality and fit of the surrogate model. If you are unhappy with the final model, try a different Measure and/or error function. See also Multi-Objective Modeling.
  • By default Matlab warnings are turned off. To turn them on, either edit configure.m or type 'warning on' before running 'go'.
  • More information on how to run the SUMO toolbox on a cluster/grid with no Matlab installation can be found here.
  • Some helpful scripts to run SUMO on a SGE (sun grid) cluster is here.
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