Model Templates
What Is a Model Template?
Models that you import
into SAS Model Manager are associated with a specific model template. A model template has properties and component files that define a type of model.
SAS Model Manager
processes four types of models: analytical, classification, prediction,
and segmentation. You can create your own model template if your model
requires files other than those named in the SAS Model Manager templates.
A model template is an XML file that has three sections. The General section
names and describes the model template. The Properties section provides properties to name the model algorithm, the modeler, and a model label. The Files section contains the component files that can be used in the template for that model function type. You associate your component file with the appropriate model template component
file. Your component file filenames do not need to be the same name as the filenames
in the model template.
Model templates provide you with a way to define metadata about your own model. Most users do not need to write model templates because SAS
Model Manager delivers a list of model templates that handle SAS Enterprise Miner models as well as analytical, prediction, classification, and segmentation models. However, you can write your own model templates if the model templates that are
provided do not satisfy your requirements. For more
information, see Creating and Managing Templates.
Model Types
SAS Model Manager provides model templates for analytical, classification, prediction,
and segmentation models.
|
Model Type
|
Description
|
|---|---|
|
Analytical
|
The Analytical model template is the most generic template that is designed for models whose model
function does not fall in the prediction, classification, and segmentation category.
|
|
Classification
|
You use the Classification model template if your model is a prediction model that has a categorical, ordinal, or binary target, or if your model is a LOGISTIC procedure regression model. Examples of classification models are models that might classify a loan applicant as Approved or Not Approved, or models
that might assess a potential customer's risk of default as Low, Medium, or High.
|
|
Prediction
|
The Prediction model template is used for predictive models. Predictive models declare in advance the outcome of an interval target. A model that assigns a numeric credit score to an applicant is an example of a prediction
model.
|
|
Segmentation
|
The Segmentation model template is used for segmentation or cluster models that are written in SAS code. Segmentation models are unsupervised models that have
no target variable. A segmentation or cluster model is designed to identify and form segments, or clusters, of individuals or observations that share some affinity for an attribute of interest. The output from a segmentation model is a set of cluster IDs. R models cannot have segmentation model function.
|
Model Template Component Files
Here is a list of the component files that are associated with the model templates:
|
Filename
|
Analytical
|
Classification
|
Prediction
|
Segmentation
|
|---|---|---|---|---|
|
—
|
 |
—
|
—
|
|
|
—
|
|
—
|
—
|
|
|
—
|
|
—
|
—
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
—
|
|
|
—
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
—
|
|
|
—
|
|
|
|
|
|
|
|
|
—
|
|
—
|
—
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
—
|
|
|
|
|
|
—
|
|
|
|
|
|
|
|
|
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
—
|
|
|
|
|
|
—
|
|
|
|
|
|
—
|
|
|
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
—
|
|
|
—
|
IGN_STATS.csv
The value of IGN_STAT.csv is the name of a file whose values are separated by commas,
and whose values are bin definitions for input variables. This is a component file that is generated by SAS Enterprise Miner for a scorecard model and is not needed for SAS code models.
EMPublishScore.sas
The value of EMPublishScore.sas is the name of a SAS code file that is used to change
input variables into bins and is a component of a SAS Enterprise Miner scorecard model. This file is needed
to define a performance task. This file is not needed for SAS code models.
Scorecard_GainsTable.csv
This file includes the bin score definitions and is not used in reporting by SAS Model Manager.
The file's content can be viewed by users.
score.sas
The value of score.sas is the name of a filename for the SAS score code for the model.
For R models, this file transforms a scoring data set to an R data frame.
The score.sas file is DATA step score code and is used as input by the SAS Scoring
Accelerator when publishing a model to a
database. When you are using the scoring function publish method, some SAS language elements and syntax are not supported when you
create or modify your score code. Only the SAS language elements and syntax that are
required to run critical data transformations and model scoring functions are available. If you use a statement or function that is not supported, an error
occurs and your model is not published to the database. For more information,
see Considerations When Creating or Modifying DATA Step Score Code in SAS In-Database Products: User’s Guide.
modelinput.sas7bdat
The value of modelinput.sas7bdat is the name of a sample data set that is used to create an inputvar.xml file for the model if one does not exist.
When no inputvar.xml file exists for the model, SAS Model Manager creates the inputvar.xml
file using the variable name and attributes in the modelinput.sas7bdat file. Observation values are not used. Therefore, the
sample data set can have no observations or it can have any number of observations.
If an inputvar.xml is specified in the
model template, modelinput.sas7bdat is ignored.
When you import a SAS code model, the data set that you used to test your score code
can be used as the value for the modelinput.sas7bdat file.
Note: If the same variables appear
in your modelinput.sas7bdat file and your modeloutput.sas7bdat file,
when you import the model, SAS Model Manager removes
the duplicate variables in the outputvar.xml file.
modeloutput.sas7bdat
The value of modeloutput.sas7bdat is the name of a sample data set that is used to
create an outputvar.xml file for the model if one does not exist.
When no outputvar.xml file exists for the model, SAS Model Manager creates the outputvar.xml
file using the variable name and attributes in the modeloutput.sas7bdat file. Observation
values are not used. Therefore, the
sample data set can have no observations or it can have any number of observations.
If an outputvar.xml is specified in the
model template, modeloutput.sas7bdat is ignored.
You can create a modeloutput.sas7bdat
file by running the score.sas file against the modelinput.sas7bdat
file.
target.sas7bdat
The value of target.sas7bdat is the name of a sample data set that is used to create
a targetvar.xml file for the model if one does not exist.
When no targetvar.xml file exists for the model, SAS Model Manager creates the targetvar.xml
file using the variable name and attributes in the target.sas7bdat file. Data set
values are not used. Therefore, the sample
data set can have no observations or it can have any number of observations. If a
targetvar.xml file is specified
in the model template, target.sas7bdat is ignored.
You can create a target.sas7bdat file by creating a data set that keeps only the target variables that are taken from the training data set, as in this example:
data mydir.target;
set mydir.myModelTraining (obs-1);
keep P_BAD;
run;
inputvar.xml
The value of inputvar.xml is the name of an XML file that defines the model input
variables. When your model template includes a file for modelinput.sas7bdat, SAS
Model Manager
creates the model inputvar.xml file. Otherwise, you must create the
XML file.
The following XML file is a sample inputvar.xml file that has one variable, CLAGE.
You can use this model to create an inputvar.xml file that contains a VARIABLE element
for each model input variable.
<?xml version="1.0" encoding="utf-8"?> <TABLE> <VARIABLE> <NAME>CLAGE</NAME> <TYPE>N</TYPE> <LENGTH>8</LENGTH> <LABEL Missing=""/> <FORMAT Missing=""/> <LEVEL>INTERVAL</LEVEL> <ROLE>INPUT</ROLE> </VARIABLE> </TABLE>
NAME
specifies the variable
name.
TYPE
specifies the variable type. Valid values are N for numeric variables and C for character variables.
LENGTH
specifies the length
of the variable.
LABEL Missing=""
specifies the character to use for missing values. The default character is a blank
space.
FORMAT Missing=""
specifies a SAS format to format the variable.
LEVEL
specifies either NOMINAL,
ORDINAL, INTERVAL, or BINARY.
ROLE
specifies INPUT for input variables.
outputvar.xml
The value of outputvar.xml is the name of an XML file that defines the model output variables. When your model template includes a file for modeloutput.sas7bdat, SAS Model Manager
creates the model outputvar.xml file. Otherwise, you must create the
XML file.
The following XML file is a sample outputvar.xml file that has one variable, I_BAD.
You can use this model to create an outputvar.xml file that contains a VARIABLE element
for each model output variable.
<?xml version="1.0" encoding="utf-8"?> <TABLE> <VARIABLE> <NAME>I_BAD</NAME> <TYPE>C</TYPE> <LENGTH>12</LENGTH> <LABEL>Into: BAD</LABEL> <FORMAT Missing=""/> <LEVEL>NOMINAL</LEVEL> <ROLE>CLASSIFICATION</ROLE> </VARIABLE> </TABLE>
NAME
specifies the variable
name.
TYPE
specifies the variable type. Valid values are N for numeric variables and C for character
variables.
LENGTH
specifies the length
of the variable.
LABEL Missing=""
specifies a label for the output variable.
FORMAT Missing=""
specifies a SAS format to format the variable.
LEVEL
specifies either NOMINAL,
ORDINAL, INTERVAL, or BINARY.
ROLE
specifies the type
of model output. Valid values are CLASSIFICATION, PREDICT, SEGMENT,
and ASSESS.
targetvar.xml
The value of targetvar.xml is the name of an XML file that defines the model target variables. When your model template includes a file for target.sas7bdat, SAS Model Manager
creates the targetvar.xml file. Otherwise, you must create the XML
file.
The following XML file is a sample targetvar.xml file that has one variable, I_BAD.
You can use this model to create an outputvar.xml file that contains a VARIABLE element
for each model output variable.
<?xml version="1.0" encoding="utf-8"?> <TABLE> <VARIABLE> <NAME>BAD</NAME> <TYPE>N</TYPE> <LENGTH>8</LENGTH> <LABEL>Missing=””/> <FORMAT Missing=""/> <LEVEL>BINARY</LEVEL> <ROLE>TARGET</ROLE> </VARIABLE> </TABLE>
NAME
specifies the variable
name.
TYPE
specifies the variable type. Valid values are N for numeric variables and C for character
variables.
LENGTH
specifies the length
of the variable.
LABEL Missing=""
specifies a label for the target variable.
FORMAT Missing=""
specifies a SAS format to format the variable.
LEVEL
specifies either NOMINAL,
ORDINAL, INTERVAL, or BINARY.
ROLE
specifies TARGET as
the value.
smmpostcode.sas
SAS Model Manager creates this file to document the mapping that the user specified
between the model variables and the project variables.
trainingvariables.csv
This optional file
contains a list of the training variables.
training.sas
This file is the optional
SAS code that was used to train the model that you are importing. If
at some time, SAS Model Manager reporting utilities
detect a shift in the distribution of model input data values or a
drift in the model's predictive capabilities, the training.sas
code can be used to retrain the model on the newer data. If it is
not available at import time, the training.sas code can be added at
a later point using the Add Local Files feature.
training.log
This file is the optional log file that was produced when the model that you are importing was trained. The information
in the optional SAS training log can be helpful if the model must be retrained in
the future.
training.lst
This file is the optional
text output that is produced when the training.sas code is run. The
information in the optional SAS training.lst table can be helpful
if the model must be retrained in the future.
outest.sas7bdat
This data set contains output estimate parameters that are produced by a few SAS procedures, including the LOGISTIC procedure.
outmodel.sas7bdat
This data set contains output data that is produced by a few SAS procedures, including the LOGISTIC procedure and the
ARBORETUM procedure. It contains complete
information for later scoring by the same SAS procedure using the SCORE statement.
output.spk
This file is the SAS package file that contains the SPK collection of model component files.
miningresult.spk
This is a SAS package file that stores detailed information about SAS Enterprise Miner
nodes in the flow from which the model is created and the detailed information for SAS/STAT item store models.
layout.xml
This optional file
contains information about the SAS Enterprise Miner diagram topology.
format.sas7bcat
This file is the optional SAS formats catalog file that contains the user-defined formats for their training data. If the model that you are importing does not use a user-defined format, then you do not need to import a format.sas7bcat catalog file.
dataprep.sas
This file contains optional SAS code that is intended to be executed before each run
of score code.
batch.sas
This file is created
by SAS Enterprise Miner and is used for model retraining by SAS Model Manager.
pmml.xml
This file contains score code in PMML format.
training.r
This is an optional
R script file that is used to retrain R models in SAS Model Manager.
outmodel.rda
SAS Model Manager requires this file to save the output parameter estimate for R models.
score.r
This file is an R script
that is used to predict new data.
fitstats.xml
This file is created
by SAS Enterprise Miner and contains the basic Fit Statistics for
the model.
HPDMForest_VARIMPORT.csv
This CSV file contains the variable importance data for a PROC HPFOREST model.
HPDMForest_ITERATION.csv
This CSV file contains statistics across each iteration of a PROC HPFOREST model.
OUTMDLFILE.bin
This is a binary file that contains the PROC HPFOREST model information to be used for scoring.
For information
about preparing R model component files, see R Model Support.
Model Template Properties
Template Properties
Here is a list of the general properties that define the model template.
|
Property Name
|
Description
|
|---|---|
|
Name
|
Identifies the name of the template. This property is required. The characters @ \ / * % # & $ ( ) ! ? < > ^ + ~ ` = { } [ ] | ; : ‘ " cannot be used in the name.
|
|
Description
|
Specifies user-defined information about the template.
|
|
Type
|
Specifies the type of
the model. SAS Model Manager
supports the following model types:
Analytical Model
specifies the type of model that is associated with the Analytical model function.
Classification Model
specifies the type of model that is associated with the Classification model function.
Prediction Model
specifies the type of model that is associated with the Prediction model function.
Clustering Model
specifies the type of model that is associated with the Segmentation model function.
|
|
Tool
|
Specifies a text value
that describes which tool is used to produce this type of model.
|
|
Validate
|
Indicates that SAS Model Manager
verifies that all of the required files are present when users try
to import a model. If validation fails, the model will not be successfully imported.
|
|
Display
name
|
Specifies a text value that is displayed as the name of the model template.
|
|
Score code
type
|
Specifies whether the imported model score code runs by using a DATA Step fragment, SAS
Program code, PMML, Analytic
store, or DS2.
|
File List Properties
Here is a list of the
File List properties that specify the files that are contained in
a model.
|
Property Name
|
Definition
|
|---|---|
|
Name
|
Identifies the name
of the file. This property is required.
|
|
Description
|
Specifies user-defined information about the file.
|
|
Required
|
When it is selected,
indicates that the file is a required component file of the model
that must be imported before using the model.
|
|
Report
|
When it is selected, indicates that the file is to be included in a SAS package file
when a model is published to a channel.
|
|
Type
|
Specifies a file whose type is text or binary.
|
|
Fileref
|
Specifies an eight-character (or fewer) SAS file reference to refer to this file in
score.sas code. The fileref
is assigned by SAS Model Manager when a
SAS job is submitted.
|
Note: All user-defined models must
have three files.
-
score.sas is the model's score code.
-
modelinput.sas7bdat is a SAS data set whose variables are used by the model score code. The contents of the data set is not used by SAS Model Manager.
-
modeloutput.sas7bdat is a resulting data set when a user runs score.sas against modelinput.sas7bdat. The data set provides output variables that the model creates after a scoring test is executed. The contents of the data set is not used by SAS Model Manager.
System and User Properties
Here is a list of the system-defined and user-defined properties for a model template.
Users can set these properties when they import a model.
|
Property Name
|
Description
|
|---|---|
|
Name
|
Identifies the name
of the property. This is a required field.
|
|
Description
|
Specifies user-defined information about the property.
|
|
Type
|
Specifies a property
whose type is String or Date.
|
|
Edit
|
Indicates that the property
can be modified when importing a model or after the model is imported.
|
|
Required
|
Indicates that the property
is required.
|
|
Initial
value
|
Specifies a text string for the initial value for the property.
|
|
Display
name
|
Specifies a text value
that is displayed as the name of the property.
|
Specific Properties
Here is a list of specific properties for a model that identify the fundamental model
data structures and some of the critical model life cycle dates. Where applicable, project-based or version-based data structures automatically
populate properties for model-based data structures.
|
Property Name
|
Description
|
|---|---|
|
Default
scoring input table
|
Specifies a default SAS data set that is used as the input data table for all of scoring
tests within the project.
The model's Default scoring
input table property inherits the property value from
the associated version or project, if one is specified.
|
|
Default
scoring output table
|
Specifies a default SAS data set that defines the variables to keep in the scoring results table and the scoring test output table. The model's Default
scoring output table property inherits the property value
from the associated version or project, if one is specified.
|
|
Default
performance table
|
Specifies the default performance table for all model performance monitoring tasks within a project.
A model's Default
performance table property inherits the property value
from the associated version or project, if one is specified. If you
do not specify a performance table, some of the monitoring reports
might not be enabled.
|
|
Default
train table
|
The train table is optional
and is used only as information. However, when a value is specified
for a model's Default train table property.
|
|
Expiration
date
|
Specifies a date property
by which the selected model is obsolete or needs to be updated or
replaced. This property is for informational purposes and is not associated
with any computational action. This property is optional.
|
|
Model label
|
Specifies a text string that is used as a label for the selected model in model assessment charts. If no value is provided for the Model Label property, the text string that is specified for the Model Name property
is used. The Model Label property can be
useful if the Model Name property that is specified is too long for
use in plots. This property is optional.
|
|
Subject
|
Specifies a text string that is used to provide an additional description for a model,
such as a promotional
or campaign code. This property is for informational purposes and is not associated
with any computational action. This property is optional.
|
|
Algorithm
|
Specifies the computational
algorithm that is used for the selected model. This property cannot
be modified.
|
|
Function
|
Specifies the function
class that was chosen when the associated project was created. The Function property specifies the type of output that models in the predictive model project generate.
|
|
Modeler
|
Specifies the Modeler ID or, when Modeler ID is missing, specifies the user ID of
the individual who created the model that is stored in the SPK file for SAS Enterprise
Miner models. Otherwise, the modeler can be specified during model import for local
files.
|
|
Tool
|
Specifies whether the
imported model came from SAS Enterprise Miner or from other modeling
tools.
|
|
Tool version
|
Specifies the version
number of the tool that is specified in the Tool property.
|
|
Score code
type
|
Specifies whether the imported model score code is a DATA step fragment, ready-to-run
SAS code, or a PMML file. Valid values are
DATA step, SAS
Program, PMML, Analytic
store, and DS2.
Note: If the model is created using
PMML 4.2 or later, the Score Code Type is DATA
step and not PMML. For more information,
see PROC PSCORE and PMML Support.
Note: SAS Model Manager cannot
publish models to a database whose Score Code Type model
property is set to SAS Program, PMML, Analytic
store, and DS2.
|
|
Template
|
Specifies the model template that was used to import the model and to create pointers
to its component files and
metadata.
|
|
Copied from
|
Specifies where the original model is if this model is copied from another model repository.
|
|
Target variable
|
Specifies the name of the target variable for a classification or prediction model.
This property can be ignored for segmentation, cluster, and other models that do not
use target variables. For example, if a model predicts when GENDER=M, then the target
variable is GENDER.
|
|
Target event
value
|
Specifies a value for the target event that the model attempts to predict. This property is used only when a value is specified
for the Target
Variable property. For example, if a model predicts when GENDER=M, then the target event value is M.
|
Copyright © SAS Institute Inc. All Rights Reserved.
Last updated: February 14, 2017