SDCROSSVAL Perform cross-validation

   S=SDCROSSVAL(ALG,DATA,options)
   [S,RES,E]=SDCROSSVAL(ALG,DATA,options)

 INPUTS
   ALG      untrained algorithm or pipeline returning decisions
   DATA     dataset to perform cross-validation on

 OPTIONS
   'method' cross-val method: rotation (def),randomization,leave-one-out
   'folds'  number of folds to perform (default: 10)
   'seed'   random seed (default: no seed set)
   'ops'    set of operating points to estimate ROC with variances

 OUTPUT
   S      String summarizing the results (mean/std for each perf.measure)
   RES    Structure with estimated performances per fold
   E      Evaluation object storing per-fold trained algorithms

 DESCRIPTION
 SDCROSSVAL performs N-fold cross-validation of untrained algorithm,
 pipeline or mapping ALG. Rotation, randomization and leave-one-out
 schemes are supported. In the default rotation mode, the DATA is split
 into N folds (splitting each class separately). Repeatedly, N-1 subsets
 are used to train ALG and the performance is estimated on the Nth subset.

 Randomization splits DATA using RANDSUBSET method. By default 50% of
 samples are used for training, the rest for testing.  The numerical value
 following the 'random' option is passed to RANDSUBSET.

 The leave-one-out is run over samples by default but may be executed
 on all unique categories of a sample property using the 'over' option.
 This allows us to cross-validate algorithm over patients or objects.

 If a set of operating point is provided using the 'ops' option,
 SDCROSSVAL estimates ROC with variances at these op.points. ALG must
 return soft output in this case.

 EXAMPLES
 Rotation over 20 folds
   S=SDCROSSVAL(ALG,DATA,'folds',20)
 Randomization, use 80% of DATA for training
   S=SDCROSSVAL(ALG,DATA,'method','rand',0.8)
 Randomization, use 100 samples per class for training
   S=SDCROSSVAL(ALG,DATA,'method','rand',100)
 Leave-one-out
   S=SDCROSSVAL(ALG,DATA,'method','loo')
 Leave-one-out over patients labels
   S=SDCROSSVAL(ALG,DATA,'method','loo','over','patient')

 READ MORE
 http://perclass.com/doc/guide/evaluation.html#intro

sdcrossval is referenced in examples:

• kb4: How to cross-validate over objects?
• kb3: Perform leave-one-out evaluation