Comparemodels: Difference between revisions

From Eigenvector Research Documentation Wiki
Jump to navigation Jump to search
imported>Scott
(Created page with "===Purpose=== Create summary table of models' performance statistics. ===Synopsis=== :[columnkeys columnlabels tablevalues] = comparemodels(models) :[columnkeys columnlabels...")
 
 
(5 intermediate revisions by 2 users not shown)
Line 11: Line 11:
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: (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).
* 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====
* '''firstout''' = first output is this.
* '''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===
Line 27: Line 28:
* '''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.

See Also

ensemble, modeloptimizer, modeloptimizergui