Modeling and Multivariate Methods - SAS

280 Creating Neural Networks Chapter 10
Overview of Neural Networks
The Neural Launch Window
Use the Neural launch window to specify X and Y variables, a validation column, and to enable missing
value coding.
Figure 10.3 The Neural Launch Window
Table 10.1 Description of the Neural Launch Window
Y, Response Choose the response variable. When multiple responses are specified, the
models for the responses share all parameters in the hidden layers (those
parameters not connected to the responses).
X, Factor Choose the input variables.
Freq
Validation
By
Missing Value
Coding
Choose a frequency variable.
Choose a validation column. For more information, see “Validation
Method” on page 282.
Choose a variable to create separate models for each level of the variable.
Check this box to enable missing value imputation and coding. If this
option is not checked, rows with missing values are ignored.
For continuous variables, missing values are replaced by the mean of the
variable. Also, a missing value indicator variable is created and included in
the model. If a variable is transformed, the imputation occurs after the
transformation.
For categorical variables, the missing values are not imputed, but are treated
as another level of the variable in the model.