SDSCATTER Interactive scatter plot and visualization of classifier outputs

 Interactive scatter plot
   SH=SDSCATTER(DATA,options)

 Visualization of pipeline outputs
   SH=SDSCATTER(DATA,P)
   SH=SDSCATTER(DATA,PD,'roc',R);

 INPUT
   DATA     data set
   P        pipeline object
   PD       pipeline object returning decisions
   R        SDROC object

 OUTPUT
   SH       handle of the scatter figure

 OPTIONS
 'callback' function handle of a callback (see prsd_example_user_callback.m)


 DESCRIPTION
 SDSCATTER provides interactive scatter plot and visualization of
 pipeline outputs. See Scatter menu for interactive functionality.
 Interactive keyboard commands:
  cursor keys : change features on x (left/right) and y (up/down) axis
  'l'  : legend on/off

 For 2D data sets, SDSCATTER can show pipeline soft outputs or decisions.
 If the SDROC object R is provided a separate ROC plot is opened and
 connected to the scatter plot. The user may then interactively change the
 opertating point and analyze the changes to classifier decisions in the
 scatter.

 READ MORE
 http://doc.prsdstudio.com/latest/guide/visualization.html#sdscatter

sdscatter is referenced in examples:

• kb18: How to protect a trained discriminant against outliers?
• kb17: How to optimize three-class classifier in imbalanced problems
• kb16: Visualize the effect of a change of parameters in a trained classifier
• kb15: How to speed up classifiers using the neural network approximation?
• kb12: Detector classifier cascade with ROC analysis
• kb11: Hierarchical classifier: How to build detector-classifier cascade?
• kb10: A step by step construction of a detector
• kb8: How to build a detector in a single line of code?
• kb7: How to convert LIBSVM Support Vector machine into a pipeline?