Plsdaroc
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Contents |
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
options = options structure that can contain the following fields
- 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)