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In principle there are two methods to select the variables for a multivariate
model to be established:
select the variables off-line: the variables are selected before
the multivariate model is set up. This is simple but may not be efficient
if the selection method does not fit the modeling method. Examples: selection
by Fisher ratio, or selection according
to correlations.
select the variables including the modeling method: the variable
selection is included in the whole modeling process. This ensures that
the variables are selected in a way which gives the best results with the
given modeling method. Examples of this approach are stepwise regression,
or growing neural networks.