MTS Action Set
Provides actions for creating and managing MTS
mtsTrain Action
Uses the Mahalanobis-Taguchi system (MTS) for training.
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parameterdata |
— |
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS). |
|
— |
specifies the optional input that contains the covariance matrix of the explanatory variables. | |
|
— |
specifies the optional input that contains the means of the input variables. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the output table to store the covariance matrix of the explanatory variables after MTS training. | |
|
— |
specifies the output table to store means of the explanatory variables after MTS training. | |
|
— |
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag. | |
|
names |
lists the names of results tables to save as CAS tables on the server. | |
|
— |
specifies the data-only analytic store from MTS training. | |
|
— |
specifies the output table that stores information necessary for MTS scoring and diagnostics. | |
|
— |
specifies the output table to store the summary statistics after MTS training. |
Parameter Descriptions
corrType="PEARSON" | "ROBUST"
cov={casouttable}
specifies the output table to store the covariance matrix of the explanatory variables after MTS training.
For more information about specifying the cov parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
cutoffFrac=double
specifies the cutoff fraction for outlier detection.
| Default | 0.05 |
|---|---|
| Range | (0, 1) |
* data={castable}
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS).
For more information about specifying the data parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
display={displayTables}
specifies a list of results tables to send to the client for display.
For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).
id="variable-name"
specifies the ID variable.
inCov={castable}
specifies the optional input that contains the covariance matrix of the explanatory variables.
For more information about specifying the inCov parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
inMean={castable}
specifies the optional input that contains the means of the input variables.
For more information about specifying the inMean parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
* input={"variable-name-1" <, "variable-name-2", ...>}
specifies the list of explanatory variables.
mean={casouttable}
specifies the output table to store means of the explanatory variables after MTS training.
For more information about specifying the mean parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outData={casouttable}
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag.
For more information about specifying the outData parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outliers=integer
specifies the optional outlier detection for MTS training.
| Default | 0 |
|---|---|
| Range | 0–1 |
outputTables={outputTables}
lists the names of results tables to save as CAS tables on the server.
For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).
| Alias | displayOut |
|---|
saveState={casouttable}
specifies the data-only analytic store from MTS training.
For more information about specifying the saveState parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
scoreInfo={casouttable}
specifies the output table that stores information necessary for MTS scoring and diagnostics.
For more information about specifying the scoreInfo parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
stat={casouttable}
specifies the output table to store the summary statistics after MTS training.
For more information about specifying the stat parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
threshold=double
specifies the Mahalanobis distance threshold to determine outliers during training.
| Default | 3 |
|---|---|
| Minimum value | 0 |
mtsTrain Action
Uses the Mahalanobis-Taguchi system (MTS) for training.
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parameterdata |
— |
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS). |
|
— |
specifies the optional input that contains the covariance matrix of the explanatory variables. | |
|
— |
specifies the optional input that contains the means of the input variables. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the output table to store the covariance matrix of the explanatory variables after MTS training. | |
|
— |
specifies the output table to store means of the explanatory variables after MTS training. | |
|
— |
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag. | |
|
names |
lists the names of results tables to save as CAS tables on the server. | |
|
— |
specifies the data-only analytic store from MTS training. | |
|
— |
specifies the output table that stores information necessary for MTS scoring and diagnostics. | |
|
— |
specifies the output table to store the summary statistics after MTS training. |
Parameter Descriptions
corrType="PEARSON" | "ROBUST"
cov={casouttable}
specifies the output table to store the covariance matrix of the explanatory variables after MTS training.
For more information about specifying the cov parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
cutoffFrac=double
specifies the cutoff fraction for outlier detection.
| Default | 0.05 |
|---|---|
| Range | (0, 1) |
* data={castable}
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS).
For more information about specifying the data parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
display={displayTables}
specifies a list of results tables to send to the client for display.
For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).
id="variable-name"
specifies the ID variable.
inCov={castable}
specifies the optional input that contains the covariance matrix of the explanatory variables.
For more information about specifying the inCov parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
inMean={castable}
specifies the optional input that contains the means of the input variables.
For more information about specifying the inMean parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
* input={"variable-name-1" <, "variable-name-2", ...>}
specifies the list of explanatory variables.
mean={casouttable}
specifies the output table to store means of the explanatory variables after MTS training.
For more information about specifying the mean parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outData={casouttable}
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag.
For more information about specifying the outData parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outliers=integer
specifies the optional outlier detection for MTS training.
| Default | 0 |
|---|---|
| Range | 0–1 |
outputTables={outputTables}
lists the names of results tables to save as CAS tables on the server.
For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).
| Alias | displayOut |
|---|
saveState={casouttable}
specifies the data-only analytic store from MTS training.
For more information about specifying the saveState parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
scoreInfo={casouttable}
specifies the output table that stores information necessary for MTS scoring and diagnostics.
For more information about specifying the scoreInfo parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
stat={casouttable}
specifies the output table to store the summary statistics after MTS training.
For more information about specifying the stat parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
threshold=double
specifies the Mahalanobis distance threshold to determine outliers during training.
| Default | 3 |
|---|---|
| Minimum value | 0 |
mtsTrain Action
Uses the Mahalanobis-Taguchi system (MTS) for training.
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parameterdata |
— |
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS). |
|
— |
specifies the optional input that contains the covariance matrix of the explanatory variables. | |
|
— |
specifies the optional input that contains the means of the input variables. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the output table to store the covariance matrix of the explanatory variables after MTS training. | |
|
— |
specifies the output table to store means of the explanatory variables after MTS training. | |
|
— |
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag. | |
|
names |
lists the names of results tables to save as CAS tables on the server. | |
|
— |
specifies the data-only analytic store from MTS training. | |
|
— |
specifies the output table that stores information necessary for MTS scoring and diagnostics. | |
|
— |
specifies the output table to store the summary statistics after MTS training. |
Parameter Descriptions
corrType="PEARSON" | "ROBUST"
cov={casouttable}
specifies the output table to store the covariance matrix of the explanatory variables after MTS training.
For more information about specifying the cov parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
cutoffFrac=double
specifies the cutoff fraction for outlier detection.
| Default | 0.05 |
|---|---|
| Range | (0, 1) |
* data={castable}
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS).
For more information about specifying the data parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
display={displayTables}
specifies a list of results tables to send to the client for display.
For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).
id="variable-name"
specifies the ID variable.
inCov={castable}
specifies the optional input that contains the covariance matrix of the explanatory variables.
For more information about specifying the inCov parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
inMean={castable}
specifies the optional input that contains the means of the input variables.
For more information about specifying the inMean parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
* input=["variable-name-1" <, "variable-name-2", ...>]
specifies the list of explanatory variables.
mean={casouttable}
specifies the output table to store means of the explanatory variables after MTS training.
For more information about specifying the mean parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outData={casouttable}
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag.
For more information about specifying the outData parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outliers=integer
specifies the optional outlier detection for MTS training.
| Default | 0 |
|---|---|
| Range | 0–1 |
outputTables={outputTables}
lists the names of results tables to save as CAS tables on the server.
For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).
| Alias | displayOut |
|---|
saveState={casouttable}
specifies the data-only analytic store from MTS training.
For more information about specifying the saveState parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
scoreInfo={casouttable}
specifies the output table that stores information necessary for MTS scoring and diagnostics.
For more information about specifying the scoreInfo parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
stat={casouttable}
specifies the output table to store the summary statistics after MTS training.
For more information about specifying the stat parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
threshold=double
specifies the Mahalanobis distance threshold to determine outliers during training.
| Default | 3 |
|---|---|
| Minimum value | 0 |
mtsTrain Action
Uses the Mahalanobis-Taguchi system (MTS) for training.
Summary: Input and Output Tables
If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
required parameterdata |
— |
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS). |
|
— |
specifies the optional input that contains the covariance matrix of the explanatory variables. | |
|
— |
specifies the optional input that contains the means of the input variables. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the output table to store the covariance matrix of the explanatory variables after MTS training. | |
|
— |
specifies the output table to store means of the explanatory variables after MTS training. | |
|
— |
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag. | |
|
names |
lists the names of results tables to save as CAS tables on the server. | |
|
— |
specifies the data-only analytic store from MTS training. | |
|
— |
specifies the output table that stores information necessary for MTS scoring and diagnostics. | |
|
— |
specifies the output table to store the summary statistics after MTS training. |
Parameter Descriptions
corrType="PEARSON" | "ROBUST"
cov=list(casouttable)
specifies the output table to store the covariance matrix of the explanatory variables after MTS training.
For more information about specifying the cov parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
cutoffFrac=double
specifies the cutoff fraction for outlier detection.
| Default | 0.05 |
|---|---|
| Range | (0, 1) |
* data=list(castable)
specifies the input data to train by using the Mahalanobis-Taguchi system (MTS).
For more information about specifying the data parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
display=list(displayTables)
specifies a list of results tables to send to the client for display.
For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).
id="variable-name"
specifies the ID variable.
inCov=list(castable)
specifies the optional input that contains the covariance matrix of the explanatory variables.
For more information about specifying the inCov parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
inMean=list(castable)
specifies the optional input that contains the means of the input variables.
For more information about specifying the inMean parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).
* input=list("variable-name-1" <, "variable-name-2", ...>)
specifies the list of explanatory variables.
mean=list(casouttable)
specifies the output table to store means of the explanatory variables after MTS training.
For more information about specifying the mean parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outData=list(casouttable)
specifies the training output data that contain the regular and normalized Mahalanobis distance and the include flag.
For more information about specifying the outData parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
outliers=integer
specifies the optional outlier detection for MTS training.
| Default | 0 |
|---|---|
| Range | 0–1 |
outputTables=list(outputTables)
lists the names of results tables to save as CAS tables on the server.
For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).
| Alias | displayOut |
|---|
saveState=list(casouttable)
specifies the data-only analytic store from MTS training.
For more information about specifying the saveState parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
scoreInfo=list(casouttable)
specifies the output table that stores information necessary for MTS scoring and diagnostics.
For more information about specifying the scoreInfo parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
stat=list(casouttable)
specifies the output table to store the summary statistics after MTS training.
For more information about specifying the stat parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).
threshold=double
specifies the Mahalanobis distance threshold to determine outliers during training.
| Default | 3 |
|---|---|
| Minimum value | 0 |