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Create a cross-validation index vector for a given method.


cvi = encodemethod(items,method,n,blocksize)

Output (cvi) is a vector containing the group number of each item.



  • items = number of items to sort into sets [e.g., size(x,1) for x a data array].
  • method = string defining the cross-validation method defined below.
  • n = number of subsets to split the data into
  • blocksize = number of items to include in each block (NOTE: blocksize for 'vet' method only)

The input parameter method can be any of the following:

'vet' : Venetian blinds. Every n-th item is grouped together. Optionally allows grouping of more than one sample together using "blocksize" input.
'con' : Contiguous blocks. Consecutive items are put into n groups.
'loo' : Leave one out. Each item is in an individual group, input (n) can be omitted.
'rnd' : Random. items are randomly split into n equal sized groups.


  • outputs = vector of integer values giving the group number of each item.


cvi = encodemethod(20,'con',4);
cvi = encodemethod(20,'vet',5,2);

See Also