File or Folder
|
Description
|
---|---|
score.sas
|
SAS language score code
created by SAS Enterprise Miner. This code can be used directly in
a SAS program. A sample program looks like this:
data testout ; set simpletest.scoredata ; %include “c:\models\simpletest\score.sas”; run; |
score.xml
|
A description of the
variables that are used and created by the scoring code. XML files
are created by a machine process for the use of machine processes.
Do not edit the XML file.
Restriction: The
maximum number of input variables for a scoring function is 128.
|
emoutput.xml
|
A
description of the final variables that are created by the scoring
code. This file can be kept for decision-making processes. These variables
include the primary classification, prediction, probability, segment,
profit, and loss variables created by a data mining process. The list
does not include intermediate variables created by the analysis. For more information
about these variables, see Fixed Variable Names.
Note: The emoutput.xml file is
not used by the scoring publishing macro.
|
scoredata.sas7bdat
|
A ten-row sample of
the scored data set showing typical cases of the input attributes,
intermediate variables, and final output variables. Use this data
set to test and debug new scoring processes.
Note: The scoredata.sas7bdat file
is not used by the scoring publishing macro.
|
traindata.sas7bdat
|
A ten-row sample table
of the training data set showing typical cases of the input attributes
used to develop the score code.
Note: The traindata.sas7bdat file
is not used by the scoring publishing macro.
|
Format Catalog
|
If the training data
contains SAS user-defined formats, the Score Code Export node creates
a format catalog. The catalog contains the user-defined formats in
the form of a lookup table. This file has an extension of .sas7bcat.
|
Role
|
Type
|
Prefix
|
Key
|
Suffix
|
Example
|
---|---|---|---|---|---|
Prediction
|
N
|
P_
|
Target variable name
|
|
P_amount
|
Probability
|
N
|
P_
|
Target variable name
|
Predicted event value
|
P_purchaseYES
P_purchaseNO
|
Classification
|
$
|
I_
|
Target variable name
|
|
I_purchase
|
Expected Profit
|
N
|
EP_
|
Target variable name
|
|
EP_conversion
|
Expected Loss
|
N
|
EL_
|
Target variable name
|
EL_conversion
|
|
Return on Investment
|
N
|
ROI_
|
Target variable name
|
|
ROI_conversion
|
Decision
|
$
|
D_
|
Target variable name
|
|
D_conversion
|
Decision Tree Leaf
|
N
|
_NODE_
|
|
|
_NODE_
|
Cluster number or SOM
cell ID
|
N
|
_SEGMENT_
|
|
|
_SEGMENT_
|
Role
|
Type
|
Fixed Name
|
Description
|
---|---|---|---|
Prediction
|
N
|
EM_PREDICTION
|
The prediction value
for an interval target.
|
Probability
|
N
|
EM_PROBABILITY
|
The probability of the
predicted classification, which can be any one of the target variable
values.
|
Probability
|
N
|
EM_EVENTPROBABILITY
|
The probability of the
target event. By default this is the first value in descending order.
This is often the event of interest. The user can control the ordering
in SAS Enterprise Miner.
|
Classification
|
$
|
EM_CLASSIFICATION
|
The predicted target
class value.
|
Expected Profit
|
N
|
EM_PROFIT
|
Based on the selected
decision.
|
Expected Loss
|
N
|
EM_LOSS
|
Based on the selected
decision.
|
Return on Investment
|
N
|
EM_ROI
|
Based on the selected
decision.
|
Decision
|
$
|
EM_DECISION
|
Optimal decision based
on a function of probability, cost, and profit or loss weights.
|
Decision Tree Leaf,
Cluster number, or SOM cell ID
|
N
|
EM_SEGMENT
|
Analytical customer
segmentation.
|
SAS DATA Step |
SAS Program |
PMML |
C |
Java |
DBMS |