Consider using PROC HPNEURAL instead of PROC NEURAL.  PROC HPNEURAL has a WEIGHT statement.  Here is an excerpt:     WEIGHT Statement WEIGHT variable | _INVERSE_PRIORS_ ; If you specify a WEIGHT statement, variable identifies a numeric variable in the input data set that contains the weight to be placed on the prediction error (the difference between the output of the network and the target value specified in the input data set) for each observation during training. If, instead of specifying a variable, you specify the keyword _INVERSE_PRIORS_, the HPNEURAL procedure calculates the weight applied to the prediction error of each nominal target variable as the total number of observations divided by the number of observations whose target class is the same as the current observation (in other words, the inverse of the fraction of the number of times that the target class occurs in the input data set). If variable is less than or equal to 0 or is missing, the observation is not used for training or for computing validation error. When validation error is computed during training, the weights on the validation observations are used even though weights are not used when scoring. The WEIGHT statement is optional. If a WEIGHT statement is not included, all observations are assigned a weight of 1.   For full documentation, go to http://support.sas.com/documentation/onlinedoc/miner/index.html, and select  SAS Enterprise Miner 14.3: High-Performance Procedures   Have a great new year. ... View more

If your flow is using a Data Partition (creating Train, Validate) node that is downstream from Drop, Filter, and Transform Variables nodes, and if you also want to include a separately defined Test data source, then the answer about where to include the Test data source depends on the degree to which the Test data source is already prepared.  There are several moving parts that can affect the answer.   If you want some assistance about debugging a specific flow, you might be best served by sending a model package to technical support.  Here is a link that you can use to open a track, and then send your model package.     https://support.sas.com/en/technical-support.html   This note tells how to create a model package. It also tells about how to work around a server error. (A model package does not include your data.) 46764 - Creating a model package (.SPK file) in SAS® Enterprise Miner(tm) http://support.sas.com/kb/46/764.html           ... View more

If you are still having a problem, then we recommend that you contact technical support.  Here is a link that you can use.     https://support.sas.com/en/technical-support.html          ... View more

We have some information on our web site about how to approach insufficient-memory errors when using Enterprise Miner.  To access the information, go to http://support.sas.com/notes . In the "Search only Samples and SAS Notes" area, enter some of the symptoms, message, or topic:      miner insufficient memory   Try this result:   61376 - Overcoming "insufficient memory ." and "parameter larger than documented limit" error messages   If the information in that note does not lead you to a resolution, then contact Technical Support for assistance.   Have a good week!     ... View more

Please contact technical support about this issue.  We recommend this link:   https://support.sas.com/en/technical-support.html#contact-technical-support    On that page. select Create A Track, and follow the steps.   Thank you.     ... View more

Mixed integer optimization is not available in Enterprise Miner.   One tip for learning what optimizations are available is to take advantage of the Adobe Advanced Search.    - Access the Reference Help and the High-Performance Procedures PDFs from this page.      http://support.sas.com/documentation/onlinedoc/miner/index.html    - Open each of those two PDFs.    - In Adobe reader, select Shift+CTRL+F (Edit -> Advanced Search).    - Enter optimization.   Adobe displays a nice Search window with all of the results. ... View more