Regression Action Set: Syntax

Provides actions for fitting linear, generalized linear, and logistic models

logisticScore Action

creates a table on the server that contains results from scoring observations by using a fitted model.

CASL Syntax

regression.logisticScore <result=results> <status=rc> /

alpha=double,

cBar="string",

casOut={

caslib="string",

compress=TRUE | FALSE,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

onDemand=TRUE | FALSE,

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

copyVars="ALL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>},

difChisq="string",

difDev="string",

display={

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

fitData=TRUE | FALSE,

h="string",

into="string",

intoCutpt=double,

ipred="string",

lcl="string",

lclm="string",

level="string",

obscat=TRUE | FALSE,

outputTables={

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=TRUE | FALSE,

replace=TRUE | FALSE

post="string",

pred="string",

predprobs=TRUE | FALSE,

resChi="string",

resDev="string",

resLik="string",

resRaw="string",

resWork="string",

restore={

caslib="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

name="table-name",

whereTable={

casLib="string"

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

role="string",

stdResChi="string",

stdResDev="string",

stdXBeta="string",

table={

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=TRUE | FALSE,

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

ucl="string",

uclm="string",

xBeta="string"

;

indicates a required parameter

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.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parameterrestore	—	restores regression models from a binary large object (BLOB).
required parametertable	—	specifies the input data table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the settings for an output table.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

alpha=double

specifies the significance level to use for the construction of confidence intervals. By default, this is set to the global significance level.

Range	(0, 1)

cBar="string"

names the confidence interval displacement, which measures the overall change in the global regression estimates that can be attributed to deleting the individual observation.

* casOut={casouttable}

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>}

specifies a list of one or more variables to be copied from the input table to the output table. You can alternatively specify the value ALL, or ALL_NUMERIC, which respectively copies all variables, or all numeric variables from the input table to the output table.

difChisq="string"

names the change in the Pearson chi-square statistic that can be attributed to deleting the individual observation.

difDev="string"

names the change in the deviance that can be attributed to deleting the individual observation.

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).

fitData=TRUE | FALSE

when set to True, specifies that the data to be scored were also used to fit the model.

Default	FALSE

h="string"

names the leverage of the observation.

Alias	hatDiag

into="string"

names the predicted response level.

intoCutpt=double

specifies the predicted event probability that determines the predicted binary response level.

Default	0.5

ipred="string"

names the individual predicted value for a cumulative link. If you do not specify any output statistics, then by default the predicted value is named _IPRED_.

Alias	ip, individual

lcl="string"

names the lower bound of a confidence interval for the linear predictor.

Alias	lowerXBeta, lowerLinP

lclm="string"

names the lower bound of a confidence interval for the mean.

Alias	lower, lowerMean

level="string"

names the ordered response level.

obscat=TRUE | FALSE

when set to True, computes multinomial output statistics at the observed response level.

Default	FALSE

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

post="string"

names the posterior predicted value.

pred="string"

names the predicted value. If you do not specify any output statistics, then by default the predicted value is named _PRED_.

Alias	p, predicted, iLink, mean

predprobs=TRUE | FALSE

when set to True, displays requested multinomial predicted probabilities as separate variables.

Default	FALSE

resChi="string"

names the Pearson chi-square residual.

Alias	pearson, pears

resDev="string"

names the deviance residual.

Alias	devResid

resLik="string"

names the likelihood residual (likelihood displacement).

Alias	likeDist, ld, resLike

resRaw="string"

names the raw residual.

Alias	r, resid, residual, rawResid

resWork="string"

names the working residual.

* restore={castable}

restores regression models from a binary large object (BLOB).

Long form	restore={name="table-name"}
Shortcut form	restore="table-name"

The castable value can be one or more of the following:

caslib="string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>}

specifies data source options.

Alias	options, dataSource

* name="table-name"

specifies the name of the input table.

whereTable={groupbytable}

specifies an input table that contains rows to use as a WHERE filter. If the vars parameter is not specified, then all the variable names that are common to the input table and the filtering table are used to find matching rows. If the where parameter for the input table and this parameter are specified, then this filtering table is applied first.

The groupbytable value can be one or more of the following:

casLib="string"

specifies the caslib for the filter table. By default, the active caslib is used.

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

specifies data source options.

Alias	options, dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the filter table.

vars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variable names to use from the filter table.

For more information about specifying the vars parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

where="where-expression"

specifies an expression for subsetting the data from the filter table.

role="string"

identifies the training, validation, and test roles for the observations.

stdResChi="string"

names the standardized Pearson chi-square residual.

Alias	adjPearson, adjPears

stdResDev="string"

names the standardized deviance residual.

Alias	stdDevResid

stdXBeta="string"

names the standard error of the linear predictor.

Alias	stdP

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

ucl="string"

names the upper bound of a confidence interval for the linear predictor.

Alias	upperXBeta, upperLinP

uclm="string"

names the upper bound of a confidence interval for the mean.

Alias	upper, upperMean

xBeta="string"

names the linear predictor.

Alias	linP

logisticScore Action

creates a table on the server that contains results from scoring observations by using a fitted model.

Lua Syntax

results, info = s:regression_logisticScore{

alpha=double,

cBar="string",

casOut={

caslib="string",

compress=true | false,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

onDemand=true | false,

promote=true | false,

replace=true | false,

replication=integer,

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

copyVars="ALL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>},

difChisq="string",

difDev="string",

display={

caseSensitive=true | false,

exclude=true | false,

excludeAll=true | false,

keyIsPath=true | false,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=true | false

fitData=true | false,

h="string",

into="string",

intoCutpt=double,

ipred="string",

lcl="string",

lclm="string",

level="string",

obscat=true | false,

outputTables={

groupByVarsRaw=true | false,

includeAll=true | false,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=true | false,

replace=true | false

post="string",

pred="string",

predprobs=true | false,

resChi="string",

resDev="string",

resLik="string",

resRaw="string",

resWork="string",

restore={

caslib="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

name="table-name",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

role="string",

stdResChi="string",

stdResDev="string",

stdXBeta="string",

table={

caslib="string",

computedOnDemand=true | false,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=true | false,

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

ucl="string",

uclm="string",

xBeta="string"

}

indicates a required parameter

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.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parameterrestore	—	restores regression models from a binary large object (BLOB).
required parametertable	—	specifies the input data table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the settings for an output table.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

alpha=double

specifies the significance level to use for the construction of confidence intervals. By default, this is set to the global significance level.

Range	(0, 1)

cBar="string"

names the confidence interval displacement, which measures the overall change in the global regression estimates that can be attributed to deleting the individual observation.

* casOut={casouttable}

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>}

difChisq="string"

names the change in the Pearson chi-square statistic that can be attributed to deleting the individual observation.

difDev="string"

names the change in the deviance that can be attributed to deleting the individual observation.

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).

fitData=true | false

when set to True, specifies that the data to be scored were also used to fit the model.

Default	false

h="string"

names the leverage of the observation.

Alias	hatDiag

into="string"

names the predicted response level.

intoCutpt=double

specifies the predicted event probability that determines the predicted binary response level.

Default	0.5

ipred="string"

names the individual predicted value for a cumulative link. If you do not specify any output statistics, then by default the predicted value is named _IPRED_.

Alias	ip, individual

lcl="string"

names the lower bound of a confidence interval for the linear predictor.

Alias	lowerXBeta, lowerLinP

lclm="string"

names the lower bound of a confidence interval for the mean.

Alias	lower, lowerMean

level="string"

names the ordered response level.

obscat=true | false

when set to True, computes multinomial output statistics at the observed response level.

Default	false

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

post="string"

names the posterior predicted value.

pred="string"

names the predicted value. If you do not specify any output statistics, then by default the predicted value is named _PRED_.

Alias	p, predicted, iLink, mean

predprobs=true | false

when set to True, displays requested multinomial predicted probabilities as separate variables.

Default	false

resChi="string"

names the Pearson chi-square residual.

Alias	pearson, pears

resDev="string"

names the deviance residual.

Alias	devResid

resLik="string"

names the likelihood residual (likelihood displacement).

Alias	likeDist, ld, resLike

resRaw="string"

names the raw residual.

Alias	r, resid, residual, rawResid

resWork="string"

names the working residual.

* restore={castable}

restores regression models from a binary large object (BLOB).

Long form	restore={name="table-name"}
Shortcut form	restore="table-name"

The castable value can be one or more of the following:

caslib="string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>}

specifies data source options.

Alias	options, dataSource

* name="table-name"

specifies the name of the input table.

whereTable={groupbytable}

The groupbytable value can be one or more of the following:

casLib="string"

specifies the caslib for the filter table. By default, the active caslib is used.

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

specifies data source options.

Alias	options, dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the filter table.

vars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variable names to use from the filter table.

For more information about specifying the vars parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

where="where-expression"

specifies an expression for subsetting the data from the filter table.

role="string"

identifies the training, validation, and test roles for the observations.

stdResChi="string"

names the standardized Pearson chi-square residual.

Alias	adjPearson, adjPears

stdResDev="string"

names the standardized deviance residual.

Alias	stdDevResid

stdXBeta="string"

names the standard error of the linear predictor.

Alias	stdP

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

ucl="string"

names the upper bound of a confidence interval for the linear predictor.

Alias	upperXBeta, upperLinP

uclm="string"

names the upper bound of a confidence interval for the mean.

Alias	upper, upperMean

xBeta="string"

names the linear predictor.

Alias	linP

logisticScore Action

creates a table on the server that contains results from scoring observations by using a fitted model.

Python Syntax

results= s.regression.logisticScore(

alpha=double,

cBar="string",

casOut={

"caslib":"string",

"compress":True | False,

"indexVars":["variable-name-1" <, "variable-name-2", ...>],

"label":"string",

"lifetime":64-bit-integer,

"maxMemSize":64-bit-integer,

"memoryFormat":"DVR" | "INHERIT" | "STANDARD",

"name":"table-name",

"onDemand":True | False,

"promote":True | False,

"replace":True | False,

"replication":integer,

"threadBlockSize":64-bit-integer,

"timeStamp":"string",

"where":["string-1" <, "string-2", ...>]

copyVars="ALL" | "ALL_NUMERIC" | ["variable-name-1" <, "variable-name-2", ...>],

difChisq="string",

difDev="string",

display={

"caseSensitive":True | False,

"exclude":True | False,

"excludeAll":True | False,

"keyIsPath":True | False,

"names":["string-1" <, "string-2", ...>],

"pathType":"LABEL" | "NAME",

"traceNames":True | False

fitData=True | False,

h="string",

into="string",

intoCutpt=double,

ipred="string",

lcl="string",

lclm="string",

level="string",

obscat=True | False,

outputTables={

"groupByVarsRaw":True | False,

"includeAll":True | False,

"names":["string-1" <, "string-2", ...>] | {"key-1":{casouttable-1} <, "key-2":{casouttable-2}, ...>},

"repeated":True | False,

"replace":True | False

post="string",

pred="string",

predprobs=True | False,

resChi="string",

resDev="string",

resLik="string",

resRaw="string",

resWork="string",

restore={

"caslib":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"name":"table-name",

"whereTable":{

"casLib":"string"

"dataSourceOptions":{adls_noreq-parameters | bigquery-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

role="string",

stdResChi="string",

stdResDev="string",

stdXBeta="string",

table={

"caslib":"string",

"computedOnDemand":True | False,

"computedVars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"groupBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"groupByMode":"NOSORT" | "REDISTRIBUTE",

"name":"table-name",

"onDemand":True | False,

"orderBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable":{

"casLib":"string"

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

ucl="string",

uclm="string",

xBeta="string"

)

indicates a required parameter

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.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parameterrestore	—	restores regression models from a binary large object (BLOB).
required parametertable	—	specifies the input data table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the settings for an output table.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

alpha=double

specifies the significance level to use for the construction of confidence intervals. By default, this is set to the global significance level.

Range	(0, 1)

cBar="string"

names the confidence interval displacement, which measures the overall change in the global regression estimates that can be attributed to deleting the individual observation.

* casOut={casouttable}

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_NUMERIC" | ["variable-name-1" <, "variable-name-2", ...>]

difChisq="string"

names the change in the Pearson chi-square statistic that can be attributed to deleting the individual observation.

difDev="string"

names the change in the deviance that can be attributed to deleting the individual observation.

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).

fitData=True | False

when set to True, specifies that the data to be scored were also used to fit the model.

Default	False

h="string"

names the leverage of the observation.

Alias	hatDiag

into="string"

names the predicted response level.

intoCutpt=double

specifies the predicted event probability that determines the predicted binary response level.

Default	0.5

ipred="string"

names the individual predicted value for a cumulative link. If you do not specify any output statistics, then by default the predicted value is named _IPRED_.

Alias	ip, individual

lcl="string"

names the lower bound of a confidence interval for the linear predictor.

Alias	lowerXBeta, lowerLinP

lclm="string"

names the lower bound of a confidence interval for the mean.

Alias	lower, lowerMean

level="string"

names the ordered response level.

obscat=True | False

when set to True, computes multinomial output statistics at the observed response level.

Default	False

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

post="string"

names the posterior predicted value.

pred="string"

names the predicted value. If you do not specify any output statistics, then by default the predicted value is named _PRED_.

Alias	p, predicted, iLink, mean

predprobs=True | False

when set to True, displays requested multinomial predicted probabilities as separate variables.

Default	False

resChi="string"

names the Pearson chi-square residual.

Alias	pearson, pears

resDev="string"

names the deviance residual.

Alias	devResid

resLik="string"

names the likelihood residual (likelihood displacement).

Alias	likeDist, ld, resLike

resRaw="string"

names the raw residual.

Alias	r, resid, residual, rawResid

resWork="string"

names the working residual.

* restore={castable}

restores regression models from a binary large object (BLOB).

Long form	restore={"name":"table-name"}
Shortcut form	restore="table-name"

The castable value can be one or more of the following:

"caslib":"string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>}

specifies data source options.

Alias	options, dataSource

* "name":"table-name"

specifies the name of the input table.

"whereTable":{groupbytable}

The groupbytable value can be one or more of the following:

"casLib":"string"

specifies the caslib for the filter table. By default, the active caslib is used.

"dataSourceOptions":{adls_noreq-parameters | bigquery-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

specifies data source options.

Alias	options, dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import_

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* "name":"table-name"

specifies the name of the filter table.

"vars":[{casinvardesc-1} <, {casinvardesc-2}, ...>]

specifies the variable names to use from the filter table.

For more information about specifying the vars parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

"where":"where-expression"

specifies an expression for subsetting the data from the filter table.

role="string"

identifies the training, validation, and test roles for the observations.

stdResChi="string"

names the standardized Pearson chi-square residual.

Alias	adjPearson, adjPears

stdResDev="string"

names the standardized deviance residual.

Alias	stdDevResid

stdXBeta="string"

names the standard error of the linear predictor.

Alias	stdP

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

ucl="string"

names the upper bound of a confidence interval for the linear predictor.

Alias	upperXBeta, upperLinP

uclm="string"

names the upper bound of a confidence interval for the mean.

Alias	upper, upperMean

xBeta="string"

names the linear predictor.

Alias	linP

logisticScore Action

creates a table on the server that contains results from scoring observations by using a fitted model.

R Syntax

results <– cas.regression.logisticScore(s,

alpha=double,

cBar="string",

casOut=list(

caslib="string",

compress=TRUE | FALSE,

indexVars=list("variable-name-1" <, "variable-name-2", ...>),

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

onDemand=TRUE | FALSE,

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

threadBlockSize=64-bit-integer,

timeStamp="string",

where=list("string-1" <, "string-2", ...>)

copyVars="ALL" | "ALL_NUMERIC" | list("variable-name-1" <, "variable-name-2", ...>),

difChisq="string",

difDev="string",

display=list(

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>),

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

fitData=TRUE | FALSE,

h="string",

into="string",

intoCutpt=double,

ipred="string",

lcl="string",

lclm="string",

level="string",

obscat=TRUE | FALSE,

outputTables=list(

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>) | list(key-1=list(casouttable-1) <, key-2=list(casouttable-2), ...>),

repeated=TRUE | FALSE,

replace=TRUE | FALSE

post="string",

pred="string",

predprobs=TRUE | FALSE,

resChi="string",

resDev="string",

resLik="string",

resRaw="string",

resWork="string",

restore=list(

caslib="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

name="table-name",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

role="string",

stdResChi="string",

stdResDev="string",

stdXBeta="string",

table=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

groupBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=TRUE | FALSE,

orderBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

ucl="string",

uclm="string",

xBeta="string"

)

indicates a required parameter

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.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parameterrestore	—	restores regression models from a binary large object (BLOB).
required parametertable	—	specifies the input data table.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the settings for an output table.
outputTables	names	lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

alpha=double

specifies the significance level to use for the construction of confidence intervals. By default, this is set to the global significance level.

Range	(0, 1)

cBar="string"

names the confidence interval displacement, which measures the overall change in the global regression estimates that can be attributed to deleting the individual observation.

* casOut=list(casouttable)

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_NUMERIC" | list("variable-name-1" <, "variable-name-2", ...>)

difChisq="string"

names the change in the Pearson chi-square statistic that can be attributed to deleting the individual observation.

difDev="string"

names the change in the deviance that can be attributed to deleting the individual observation.

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).

fitData=TRUE | FALSE

when set to True, specifies that the data to be scored were also used to fit the model.

Default	FALSE

h="string"

names the leverage of the observation.

Alias	hatDiag

into="string"

names the predicted response level.

intoCutpt=double

specifies the predicted event probability that determines the predicted binary response level.

Default	0.5

ipred="string"

names the individual predicted value for a cumulative link. If you do not specify any output statistics, then by default the predicted value is named _IPRED_.

Alias	ip, individual

lcl="string"

names the lower bound of a confidence interval for the linear predictor.

Alias	lowerXBeta, lowerLinP

lclm="string"

names the lower bound of a confidence interval for the mean.

Alias	lower, lowerMean

level="string"

names the ordered response level.

obscat=TRUE | FALSE

when set to True, computes multinomial output statistics at the observed response level.

Default	FALSE

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

post="string"

names the posterior predicted value.

pred="string"

names the predicted value. If you do not specify any output statistics, then by default the predicted value is named _PRED_.

Alias	p, predicted, iLink, mean

predprobs=TRUE | FALSE

when set to True, displays requested multinomial predicted probabilities as separate variables.

Default	FALSE

resChi="string"

names the Pearson chi-square residual.

Alias	pearson, pears

resDev="string"

names the deviance residual.

Alias	devResid

resLik="string"

names the likelihood residual (likelihood displacement).

Alias	likeDist, ld, resLike

resRaw="string"

names the raw residual.

Alias	r, resid, residual, rawResid

resWork="string"

names the working residual.

* restore=list(castable)

restores regression models from a binary large object (BLOB).

Long form	restore=list(name="table-name")
Shortcut form	restore="table-name"

The castable value can be one or more of the following:

caslib="string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>)

specifies data source options.

Alias	options, dataSource

* name="table-name"

specifies the name of the input table.

whereTable=list(groupbytable)

The groupbytable value can be one or more of the following:

casLib="string"

specifies the caslib for the filter table. By default, the active caslib is used.

dataSourceOptions=list(adls_noreq-parameters | bigquery-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters)

specifies data source options.

Alias	options, dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

importOptions=list(fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters)

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the filter table.

vars=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

specifies the variable names to use from the filter table.

For more information about specifying the vars parameter, see the common casinvardesc parameter (Appendix A: Common Parameters).

where="where-expression"

specifies an expression for subsetting the data from the filter table.

role="string"

identifies the training, validation, and test roles for the observations.

stdResChi="string"

names the standardized Pearson chi-square residual.

Alias	adjPearson, adjPears

stdResDev="string"

names the standardized deviance residual.

Alias	stdDevResid

stdXBeta="string"

names the standard error of the linear predictor.

Alias	stdP

* table=list(castable)

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

ucl="string"

names the upper bound of a confidence interval for the linear predictor.

Alias	upperXBeta, upperLinP

uclm="string"

names the upper bound of a confidence interval for the mean.

Alias	upper, upperMean

xBeta="string"

names the linear predictor.

Alias	linP

Last updated: November 02, 2020