names the SAS data set that contains the training and validation observations to be used by PROC HPNEURAL to train the neural network or that contains the observations to be scored when you are performing stand-alone scoring. The default input data set is the most recently created data set.
When you use PROC HPNEURAL to train a neural network, each observation must contain the input, weight, validation, ID, and target variables that are specified in the associated INPUT, WEIGHT, PARTITION, ID, and TARGET statements.
When you use PROC HPNEURAL to perform stand-alone scoring, the input data set must contain the input variables that were specified when the network was trained (as saved in the model data set) and optionally the target variables that were specified when the network was trained. In addition, if you applied formats to variables when training, the same formats must be applied when you do stand-alone scoring. Only the target variables (if they exist), the ID variables (if any exist), and the network’s predictions are written to the output data set, which is specified in the SCORE statement.
For nominal variables of character type, levels are truncated to 32 bytes and converted to uppercase. Also, when you train a network, if all observations that have a specific level for a nominal variable contain missing values in other input, target, weight, or validation variables, then that specific level is discarded and does not appear in the analysis.
The input data set must fit into the available memory of the machine.