One data entry is is left out at a time and its value predicted after
complete neural network calculations determined by the ANALYSIS
keyword, i.e., after fit or pruning of input variables in the remaining
data set. This procedure is repeated for all data entries. The **LOO**
calculations, however, are quite time demanding, since one complete
ANALYSIS
should be done for each data entry.

The neural network program also performs embedded virtual LOO (see Tetko
et al, 1995) for **random** option inPARTITION.
Both approaches provide very similar results using **fit** option in
ANALYSIS.
i.e. when validation of neural networks for the pre-set number of input
variables is used. However, the results of virtual LOO if the **pruning**
option is selected in ANALYSIS, only corresponds
to validation of the variables selected by the pruning and are not comparable
with those of the full **LOO** procedure.