Provides actions for fitting linear, generalized linear, and logistic models
computes indices of rank correlation between predicted probabilities and observed responses used for assessing the predictive ability of a model.
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 parameterrestore |
— |
restores regression models from a binary large object (BLOB). |
|
required parametertable |
— |
specifies the input data table. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the settings for an output table. |
|
|
names |
lists the names of results tables to save as CAS tables on the server. |
includes and names the accuracy in the classification table.
when set to True, requests all available statistics.
| Default | FALSE |
|---|
when sent to True, creates the association table.
| Default | TRUE |
|---|
specifies the precision of the predicted probabilities that are used for classification.
| Default | 1E-05 |
|---|---|
| Range | 0–1 |
specifies the settings for an output table.
| Long form | casOut={name="table-name"} |
|---|---|
| Shortcut form | casOut="table-name" |
The casouttable value can be one or more of the following:
specifies the list of variables to create indexes for in the output data.
specifies the descriptive label to associate with the table.
specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.
| Default | 0 |
|---|---|
| Minimum value | 0 |
specifies the maximum amount of memory, in bytes, that each thread should allocate for in-memory blocks before converting to a memory-mapped file. Files are written in the directories that are specified in the CAS_DISK_CACHE environment variable.
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
|---|
specifies the memory format for the output table.
| Default | INHERIT |
|---|
use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.
specifies the name for the output table.
when set to True, overwrites an existing table that has the same name.
| Default | FALSE |
|---|
specifies the number of copies of the table to make for fault tolerance. Larger values result in slower performance and use more memory, but provide high availability for data in the event of a node failure. Data redundancy applies to distributed servers only.
| Default | 1 |
|---|---|
| Minimum value | 0 |
specifies the number of bytes to use for blocks in the output table. The blocks are read by threads. Gradually increase this value when you have a large table with millions or billions of rows and you are tuning for performance. Larger values can increase performance with indexed tables. However, if the value is too large, then you can cause thread starvation due to too few blocks for threads to work on.
| Alias | blockSize |
|---|---|
| Default | 1048576 |
| Minimum value | 0 |
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
specifies to add a timestamp column to the table. Support for timeStamp is action-specific. Specify the value in the form that is appropriate for your session locale.
specifies one or more expressions for subsetting the output data. When multiple expressions are specified, the expressions are effectively combined using AND to form the final output filter. If an expression contains quoted values, use nested quotation marks.
creates the classification table.
| Default | FALSE |
|---|
specifies cutpoints for the classification table.
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).
when set to True, specifies that the data to be scored were also used to fit the model.
| Default | FALSE |
|---|
includes and names the false negative fraction in the classification table.
includes and names the false positive fraction (1-specificity) in the classification table.
includes and names the lift in the classification table.
includes and names the misclassification rate in the classification table.
when set to True, removes counts from the classification table.
| Default | FALSE |
|---|
includes and names the negative predictive value in the classification table.
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 |
|---|
includes and names the percent correct in the classification table.
includes and names the positive predictive value (precision) in the classification table.
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:
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.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
specifies the name of the input table.
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:
specifies the caslib for the filter table. By default, the active caslib is used.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common 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).
specifies the name of the filter table.
specifies the variable names to use from the filter table.
The casinvardesc value can be one or more of the following:
specifies the format to apply to the variable.
specifies the length of the format field plus the length of the format precision.
specifies the descriptive label for the variable.
specifies the name for the variable.
specifies the length of the format precision.
specifies the length of the format field.
specifies an expression for subsetting the data from the filter table.
specifies the input data table.
For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).
includes and names the true negative fraction (specificity) in the classification table.
includes and names the true positive fraction (recall, sensitivity) in the classification table.
computes indices of rank correlation between predicted probabilities and observed responses used for assessing the predictive ability of a model.
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 parameterrestore |
— |
restores regression models from a binary large object (BLOB). |
|
required parametertable |
— |
specifies the input data table. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the settings for an output table. |
|
|
names |
lists the names of results tables to save as CAS tables on the server. |
includes and names the accuracy in the classification table.
when set to True, requests all available statistics.
| Default | false |
|---|
when sent to True, creates the association table.
| Default | true |
|---|
specifies the precision of the predicted probabilities that are used for classification.
| Default | 1E-05 |
|---|---|
| Range | 0–1 |
specifies the settings for an output table.
| Long form | casOut={name="table-name"} |
|---|---|
| Shortcut form | casOut="table-name" |
The casouttable value can be one or more of the following:
specifies the list of variables to create indexes for in the output data.
specifies the descriptive label to associate with the table.
specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.
| Default | 0 |
|---|---|
| Minimum value | 0 |
specifies the maximum amount of memory, in bytes, that each thread should allocate for in-memory blocks before converting to a memory-mapped file. Files are written in the directories that are specified in the CAS_DISK_CACHE environment variable.
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
|---|
specifies the memory format for the output table.
| Default | INHERIT |
|---|
use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.
specifies the name for the output table.
when set to True, overwrites an existing table that has the same name.
| Default | false |
|---|
specifies the number of copies of the table to make for fault tolerance. Larger values result in slower performance and use more memory, but provide high availability for data in the event of a node failure. Data redundancy applies to distributed servers only.
| Default | 1 |
|---|---|
| Minimum value | 0 |
specifies the number of bytes to use for blocks in the output table. The blocks are read by threads. Gradually increase this value when you have a large table with millions or billions of rows and you are tuning for performance. Larger values can increase performance with indexed tables. However, if the value is too large, then you can cause thread starvation due to too few blocks for threads to work on.
| Alias | blockSize |
|---|---|
| Default | 1048576 |
| Minimum value | 0 |
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
specifies to add a timestamp column to the table. Support for timeStamp is action-specific. Specify the value in the form that is appropriate for your session locale.
specifies one or more expressions for subsetting the output data. When multiple expressions are specified, the expressions are effectively combined using AND to form the final output filter. If an expression contains quoted values, use nested quotation marks.
creates the classification table.
| Default | false |
|---|
specifies cutpoints for the classification table.
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).
when set to True, specifies that the data to be scored were also used to fit the model.
| Default | false |
|---|
includes and names the false negative fraction in the classification table.
includes and names the false positive fraction (1-specificity) in the classification table.
includes and names the lift in the classification table.
includes and names the misclassification rate in the classification table.
when set to True, removes counts from the classification table.
| Default | false |
|---|
includes and names the negative predictive value in the classification table.
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 |
|---|
includes and names the percent correct in the classification table.
includes and names the positive predictive value (precision) in the classification table.
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:
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.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
specifies the name of the input table.
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:
specifies the caslib for the filter table. By default, the active caslib is used.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common 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).
specifies the name of the filter table.
specifies the variable names to use from the filter table.
The casinvardesc value can be one or more of the following:
specifies the format to apply to the variable.
specifies the length of the format field plus the length of the format precision.
specifies the descriptive label for the variable.
specifies the name for the variable.
specifies the length of the format precision.
specifies the length of the format field.
specifies an expression for subsetting the data from the filter table.
specifies the input data table.
For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).
includes and names the true negative fraction (specificity) in the classification table.
includes and names the true positive fraction (recall, sensitivity) in the classification table.
computes indices of rank correlation between predicted probabilities and observed responses used for assessing the predictive ability of a model.
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 parameterrestore |
— |
restores regression models from a binary large object (BLOB). |
|
required parametertable |
— |
specifies the input data table. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the settings for an output table. |
|
|
names |
lists the names of results tables to save as CAS tables on the server. |
includes and names the accuracy in the classification table.
when set to True, requests all available statistics.
| Default | False |
|---|
when sent to True, creates the association table.
| Default | True |
|---|
specifies the precision of the predicted probabilities that are used for classification.
| Default | 1E-05 |
|---|---|
| Range | 0–1 |
specifies the settings for an output table.
| Long form | casOut={"name":"table-name"} |
|---|---|
| Shortcut form | casOut="table-name" |
The casouttable value can be one or more of the following:
specifies the list of variables to create indexes for in the output data.
specifies the descriptive label to associate with the table.
specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.
| Default | 0 |
|---|---|
| Minimum value | 0 |
specifies the maximum amount of memory, in bytes, that each thread should allocate for in-memory blocks before converting to a memory-mapped file. Files are written in the directories that are specified in the CAS_DISK_CACHE environment variable.
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
|---|
specifies the memory format for the output table.
| Default | INHERIT |
|---|
use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.
specifies the name for the output table.
when set to True, overwrites an existing table that has the same name.
| Default | False |
|---|
specifies the number of copies of the table to make for fault tolerance. Larger values result in slower performance and use more memory, but provide high availability for data in the event of a node failure. Data redundancy applies to distributed servers only.
| Default | 1 |
|---|---|
| Minimum value | 0 |
specifies the number of bytes to use for blocks in the output table. The blocks are read by threads. Gradually increase this value when you have a large table with millions or billions of rows and you are tuning for performance. Larger values can increase performance with indexed tables. However, if the value is too large, then you can cause thread starvation due to too few blocks for threads to work on.
| Alias | blockSize |
|---|---|
| Default | 1048576 |
| Minimum value | 0 |
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
specifies to add a timestamp column to the table. Support for timeStamp is action-specific. Specify the value in the form that is appropriate for your session locale.
specifies one or more expressions for subsetting the output data. When multiple expressions are specified, the expressions are effectively combined using AND to form the final output filter. If an expression contains quoted values, use nested quotation marks.
creates the classification table.
| Default | False |
|---|
specifies cutpoints for the classification table.
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).
when set to True, specifies that the data to be scored were also used to fit the model.
| Default | False |
|---|
includes and names the false negative fraction in the classification table.
includes and names the false positive fraction (1-specificity) in the classification table.
includes and names the lift in the classification table.
includes and names the misclassification rate in the classification table.
when set to True, removes counts from the classification table.
| Default | False |
|---|
includes and names the negative predictive value in the classification table.
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 |
|---|
includes and names the percent correct in the classification table.
includes and names the positive predictive value (precision) in the classification table.
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:
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.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
specifies the name of the input table.
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:
specifies the caslib for the filter table. By default, the active caslib is used.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common 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).
specifies the name of the filter table.
specifies the variable names to use from the filter table.
The casinvardesc value can be one or more of the following:
specifies the format to apply to the variable.
specifies the length of the format field plus the length of the format precision.
specifies the descriptive label for the variable.
specifies the name for the variable.
specifies the length of the format precision.
specifies the length of the format field.
specifies an expression for subsetting the data from the filter table.
specifies the input data table.
For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).
includes and names the true negative fraction (specificity) in the classification table.
includes and names the true positive fraction (recall, sensitivity) in the classification table.
computes indices of rank correlation between predicted probabilities and observed responses used for assessing the predictive ability of a model.
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 parameterrestore |
— |
restores regression models from a binary large object (BLOB). |
|
required parametertable |
— |
specifies the input data table. |
|
Parameter |
Subparameter |
Description |
|---|---|---|
|
— |
specifies the settings for an output table. |
|
|
names |
lists the names of results tables to save as CAS tables on the server. |
includes and names the accuracy in the classification table.
when set to True, requests all available statistics.
| Default | FALSE |
|---|
when sent to True, creates the association table.
| Default | TRUE |
|---|
specifies the precision of the predicted probabilities that are used for classification.
| Default | 1E-05 |
|---|---|
| Range | 0–1 |
specifies the settings for an output table.
| Long form | casOut=list(name="table-name") |
|---|---|
| Shortcut form | casOut="table-name" |
The casouttable value can be one or more of the following:
specifies the list of variables to create indexes for in the output data.
specifies the descriptive label to associate with the table.
specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.
| Default | 0 |
|---|---|
| Minimum value | 0 |
specifies the maximum amount of memory, in bytes, that each thread should allocate for in-memory blocks before converting to a memory-mapped file. Files are written in the directories that are specified in the CAS_DISK_CACHE environment variable.
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
|---|
specifies the memory format for the output table.
| Default | INHERIT |
|---|
use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.
specifies the name for the output table.
when set to True, overwrites an existing table that has the same name.
| Default | FALSE |
|---|
specifies the number of copies of the table to make for fault tolerance. Larger values result in slower performance and use more memory, but provide high availability for data in the event of a node failure. Data redundancy applies to distributed servers only.
| Default | 1 |
|---|---|
| Minimum value | 0 |
specifies the number of bytes to use for blocks in the output table. The blocks are read by threads. Gradually increase this value when you have a large table with millions or billions of rows and you are tuning for performance. Larger values can increase performance with indexed tables. However, if the value is too large, then you can cause thread starvation due to too few blocks for threads to work on.
| Alias | blockSize |
|---|---|
| Default | 1048576 |
| Minimum value | 0 |
| TIP | You can enclose the value in quotation marks and specify B, K, M, G, or T as a suffix to indicate the units. For example, "8M" specifies eight megabytes. |
specifies to add a timestamp column to the table. Support for timeStamp is action-specific. Specify the value in the form that is appropriate for your session locale.
specifies one or more expressions for subsetting the output data. When multiple expressions are specified, the expressions are effectively combined using AND to form the final output filter. If an expression contains quoted values, use nested quotation marks.
creates the classification table.
| Default | FALSE |
|---|
specifies cutpoints for the classification table.
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).
when set to True, specifies that the data to be scored were also used to fit the model.
| Default | FALSE |
|---|
includes and names the false negative fraction in the classification table.
includes and names the false positive fraction (1-specificity) in the classification table.
includes and names the lift in the classification table.
includes and names the misclassification rate in the classification table.
when set to True, removes counts from the classification table.
| Default | FALSE |
|---|
includes and names the negative predictive value in the classification table.
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 |
|---|
includes and names the percent correct in the classification table.
includes and names the positive predictive value (precision) in the classification table.
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:
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.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
specifies the name of the input table.
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:
specifies the caslib for the filter table. By default, the active caslib is used.
specifies data source options.
| Aliases | options |
|---|---|
| dataSource |
For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common 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).
specifies the name of the filter table.
specifies the variable names to use from the filter table.
The casinvardesc value can be one or more of the following:
specifies the format to apply to the variable.
specifies the length of the format field plus the length of the format precision.
specifies the descriptive label for the variable.
specifies the name for the variable.
specifies the length of the format precision.
specifies the length of the format field.
specifies an expression for subsetting the data from the filter table.
specifies the input data table.
For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).
includes and names the true negative fraction (specificity) in the classification table.
includes and names the true positive fraction (recall, sensitivity) in the classification table.