Comparemodels: Difference between revisions
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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. | 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: | The table shows: | ||
* Parameters- parameters and important options from each model (LVs, PCs, gamma, number of points, etc). | * Parameters - parameters and important options from each model (LVs, PCs, gamma, number of points, etc). | ||
* Statistics | * 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). | ||
====Inputs==== | ====Inputs==== | ||
* '''models''' = a cell array containing one or more models. | * '''models''' = a cell array containing one or more models. | ||
====Outputs==== | ====Outputs==== | ||
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* '''plots''': [ 'final' | {'none'} ] governs level of plotting. | * '''plots''': [ 'final' | {'none'} ] governs level of plotting. | ||
* '''category''': [ {'all'} | 'classification' | 'regression' | 'decomposition' ] restrict output to models of this category type, or all. | * '''category''': [ {'all'} | 'classification' | 'regression' | 'decomposition' ] restrict output to models of this category type, or all. | ||
===See Also=== | ===See Also=== | ||
[[modeloptimizer]], [[modeloptimizergui]] | :[[ensemble]], [[modeloptimizer]], [[modeloptimizergui]] | ||
Latest revision as of 10:31, 25 September 2024
Purpose
Create summary table of models' performance statistics.
Synopsis
- [columnkeys columnlabels tablevalues] = comparemodels(models)
- [columnkeys columnlabels tablevalues] = comparemodels(models,options)
Description
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).
Inputs
- models = a cell array containing one or more models.
Outputs
- 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
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.