Splitcaltest

Purpose

Splits data into calibration and test sets.

Synopsis

z = splitcaltest(model,options); %identifies model (calibration step)

Also available in the Analysis interface via the data context menu

Description

The split is based on the scores from the input model. If a matrix or DataSet is passed in place of a model, it is assumed to contain the scores for the data. A randomization is used in the splitting process so no assumption about the data acquisition order is necessary.

Inputs

• model = standard model structure from a factor-based model OR a double or DataSet object containing the scores to analyze.

Outputs

• z = a structure containing the class and classlookup table.

Options

• options = structure array with the following fields :

• plots: [ 'none' | {'final'} ] governs level of plotting

• algorithm: [ {'onion'} ]

• nonion: [ {3} ] the number of 'external layers'

• fraction: [ {0.66} ] fraction of data to be set as calibrations samples.

See Also

crossval, pca, pcr, preprocess.