Neural Network Action Set
Generate Stand-Alone SAS Score Code for Neural Network Model
This section contains PROC CAS code.
Note: Input data must be in a CAS table that is accessible in your CAS session. This table has a two-level name; the first level is your CAS engine libref and the second level is the table name. You refer to this table in the CAS procedure by specifying only the second level. For more information about PROC CAS, see SAS Cloud Analytic Services: CAS Procedure Programming Guide and Reference. For more information about two-level names, see Chapter 2: Shared Concepts in SAS Visual Data Mining and Machine Learning 8.1: Data Mining and Machine Learning Procedures.
After you train and validate a neural network model, you can use the model to score new data. You can score new data in more than one way. One way is to submit new data and then run the model to score the data by using your data mining environment via SAS Enterprise Miner or SAS Visual Data Mining and Machine Learning to produce scored output.
This example shows how to use the neuralNet.annCode action to generate stand-alone SAS scoring code for an ANN model. The SAS score code can be run in a SAS environment that does not have a SAS data mining solution license.
proc cas;
neuralNet.anncode /
code={labelId=1,comment=TRUE},
modelTable={name="nnet_train_model"}
listNode="OUTPUT";
run;
Generate Stand-Alone SAS Score Code for a Neural Network Model
This section contains Lua code. For more information about coding in Lua, see SAS Cloud Analytic Services: Getting Started with Python and Lua.
After you train and validate a neural network model, you can use the model to score new data. You can score new data in more than one way. One way is to submit new data and then run the model to score the data by using your data mining environment via SAS Enterprise Miner or SAS Visual Data Mining and Machine Learning to produce scored output.
This example shows how to use the neuralNet.annCode action to generate stand-alone SAS scoring code for an ANN model. The SAS score code can be run in a SAS environment that does not have a SAS data mining solution license.
results = s:neuralNet_annCode{
code={
labelId=1,
comment=True},
modelTable={
name="nnet_train_model"},
listNode="OUTPUT"
}
Generate Stand-Alone SAS Score Code for a Neural Network Model
This section contains Python code. For more information about coding in Python, see SAS Cloud Analytic Services: Getting Started with Python and Lua.
After you train and validate a neural network model, you can use the model to score new data. You can score new data in more than one way. One way is to submit new data and then run the model to score the data by using your data mining environment via SAS Enterprise Miner or SAS Visual Data Mining and Machine Learning to produce scored output.
This example shows how to use the neuralNet.annCode action to generate stand-alone SAS scoring code for an ANN model. The SAS score code can be run in a SAS environment that does not have a SAS data mining solution license.
results = s.neuralNet.annCode(
code={
"labelId":1,
"comment":True},
modelTable={
"name":"nnet_train_model"},
listNode="OUTPUT"
)
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