After you click OK in the platform launch window (or Run in the Fit Model window), the Model Launch control panel appears.
Partial Least Squares Model Launch Control Panel
Select the type of model fitting algorithm. There are two algorithm choices: NIPALS and SIMPLS. The two methods produce the same coefficient estimates when there is only one response variable. See Statistical Details for details about differences between the two algorithms.
Holdback Randomly selects the specified proportion of the data for a validation set, and uses the other portion of the data to fit the model.
KFold Partitions the data into K subsets, or folds. In turn, each fold is used to validate the model that is fit to the rest of the data, fitting a total of K models. This method is best for small data sets because it makes efficient use of limited amounts of data.
Leave-One-Out Performs leave-one-out cross validation.
None Does not use validation to choose the number of factors to extract. The number of factors is specified in the Factor Search Range.
Appears once you click Go to fit an initial model. Specify a number of factors to be used in fitting a new model.