The logisticScore action creates a table on the server that contains results from scoring observations by using a fitted model.
| Parameter | Description |
|---|---|
| alpha | specifies the significance level to use for the construction of confidence intervals. By default, this is set to the global significance level. |
| casOut | specifies the settings for an output table. |
| cBar | names the confidence interval displacement, which measures the overall change in the global regression estimates that can be attributed to deleting the individual observation. |
| copyVars | 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 | names the change in the Pearson chi-square statistic that can be attributed to deleting the individual observation. |
| difDev | names the change in the deviance that can be attributed to deleting the individual observation. |
| display | specifies a list of results tables to send to the client for display. |
| fitData | when set to True, specifies that the data to be scored were also used to fit the model. |
| h | names the leverage of the observation. |
| into | names the predicted response level. |
| intoCutpt | specifies the predicted event probability that determines the predicted binary response level. |
| ipred | 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_. |
| lcl | names the lower bound of a confidence interval for the linear predictor. |
| lclm | names the lower bound of a confidence interval for the mean. |
| level | names the ordered response level. |
| obscat | when set to True, computes multinomial output statistics at the observed response level. |
| outputTables | lists the names of results tables to save as CAS tables on the server. |
| post | names the posterior predicted value. |
| pred | names the predicted value. If you do not specify any output statistics, then by default the predicted value is named _PRED_. |
| predprobs | when set to True, displays requested multinomial predicted probabilities as separate variables. |
| resChi | names the Pearson chi-square residual. |
| resDev | names the deviance residual. |
| resLik | names the likelihood residual (likelihood displacement). |
| resRaw | names the raw residual. |
| restore | restores regression models from a binary large object (BLOB). |
| resWork | names the working residual. |
| role | identifies the training, validation, and test roles for the observations. |
| stdResChi | names the standardized Pearson chi-square residual. |
| stdResDev | names the standardized deviance residual. |
| stdXBeta | names the standard error of the linear predictor. |
| table | specifies the input data table. |
| ucl | names the upper bound of a confidence interval for the linear predictor. |
| uclm | names the upper bound of a confidence interval for the mean. |
| xBeta | names the linear predictor. |