Plsdaroc: Difference between revisions

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===Purpose===
===Purpose===


Calculate and display ROC curves for PLSDA model.
Calculate and display ROC curves for a PLSDA model.


===Synopsis===
===Synopsis===
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===Description===
===Description===


ROC curves can be used to assess the specificity and sensitivity possible with different predicted y-value thresholds for a PLSDA model. Inputs are a PLSDA model model, an optional index into the y-columns used in the model ycol [default = all columns], and an options structure. Output is a dataset with the sensitivity/specificity data roc.
ROC curves can be used to visualize the specificities and sensitivities that are possible with different predicted y-value thresholds in a PLSDA model.  
 
====Inputs====
 
* '''model''' = a PLSDA model structure
 
====Optional Inputs====
 
* '''ycol''' = an optional index into the y-columns used in the PLSDA model ycol [default = all columns],
* '''options''' = options structure (see below)
 
====Outputs====
 
* '''roc''' = dataset with the sensitivity/specificity results that are needed to plot ROC curves.


===Options===
===Options===


* '''plots''' :  [ 'none' | {'final'}]    governs plotting on/off  
* '''plots''' :  [ 'none' | {'final'}]    governs plotting on/off  
* '''figure''' : [ 'new' | 'gui' | figure_handle ] governs location for plot
** 'new' plots onto a new figure
** 'gui' plots using noninteger figure handle
** A figure handle 'figure_handle' specifies the figure onto which the plot should be made.
* '''plotstyle''' : [ 'roc' | 'threshold' | {'all'} ] governs type of plots.
** 'roc' and 'threshold' give only the specified type of plot
** 'all' shows both types of plots on one figure (default).
** '''plotstyle''' can also be specified as '1' (which gives 'roc' plots) or 2 (which gives 'threshold' plots)


===See Also===
===See Also===


[[discrimprob]], [[plsda]], [[plsdthres]], [[simca]]
[[discrimprob]], [[plsda]], [[plsdthres]], [[simca]]

Revision as of 17:45, 8 October 2008

Purpose

Calculate and display ROC curves for a PLSDA model.

Synopsis

roc = plsdaroc(model,ycol,options)

Description

ROC curves can be used to visualize the specificities and sensitivities that are possible with different predicted y-value thresholds in a PLSDA model.

Inputs

  • model = a PLSDA model structure

Optional Inputs

  • ycol = an optional index into the y-columns used in the PLSDA model ycol [default = all columns],
  • options = options structure (see below)

Outputs

  • roc = dataset with the sensitivity/specificity results that are needed to plot ROC curves.

Options

  • plots : [ 'none' | {'final'}] governs plotting on/off
  • figure : [ 'new' | 'gui' | figure_handle ] governs location for plot
    • 'new' plots onto a new figure
    • 'gui' plots using noninteger figure handle
    • A figure handle 'figure_handle' specifies the figure onto which the plot should be made.
  • plotstyle : [ 'roc' | 'threshold' | {'all'} ] governs type of plots.
    • 'roc' and 'threshold' give only the specified type of plot
    • 'all' shows both types of plots on one figure (default).
    • plotstyle can also be specified as '1' (which gives 'roc' plots) or 2 (which gives 'threshold' plots)

See Also

discrimprob, plsda, plsdthres, simca