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Create summary table of models' performance statistics.


[columnkeys columnlabels tablevalues] = comparemodels(models)
[columnkeys columnlabels tablevalues] = comparemodels(models,options)


Generate a table which summarizes the performance of a set of input models, and also shows their relevant input parameters and options. This is useful for comparing the quality of a set of models. The table shows:

  • Parameters - parameters and important options from each model (LVs, PCs, gamma, number of points, etc).
  • Statistics - (RMSEC/CV/P, # of support vectors, classification error rates as False Pos/Neg Rate average over classes. In all cases, value must be a single value for a given model (no vectors). Models which are not in the supported model list are ignored (see getallowedmodeltypes).


  • models = a cell array containing one or more models.


  • columnkeys = 1 x ncolumn cell array containing keys identifying table columns in order.
  • columnlabels = 1 x ncolumn cell array containing descriptive labels for table columns in order.
  • tablevalues = nmodel x ncolumn cell array containing values.


options = a structure array with the following fields:

  • display: [ 'off' | {'on'} ] governs level of display to command window.
  • plots: [ 'final' | {'none'} ] governs level of plotting.
  • category: [ {'all'} | 'classification' | 'regression' | 'decomposition' ] restrict output to models of this category type, or all.

See Also

modeloptimizer, modeloptimizergui