Regression Evaluator (DB)
Computes several commonly used statistical tests to determine the accuracy of several columns (Predicted Values). These represent predictions against one column (Actual Value), which is specified as the "ground truth."
Information at a Glance
|
Parameter |
Description |
|---|---|
| Category | Model Validation |
| Data source type | DB |
| Send output to other operators | No |
| Data processing tool | n/a |
Note: The Regression Evaluator (DB) operator is for database data only. For Hadoop data, use the
Regression Evaluator (HD) operator.
For information about the metrics used in this operator, see Computed Metrics and Use Case for the Regression Evaluator.
Input
A tabular data set from a database that contains a numeric column of actual values (known truth) and numeric column(s) of predicted values.
Configuration
| Parameter | Description |
|---|---|
| Notes | Notes or helpful information about this operator's parameter settings. When you enter content in the Notes field, a yellow asterisk appears on the operator. |
| Actual Value | A numeric column that holds the dependent variable that the models were used to train on, or a column of known values for the dependent variable. |
| Predicted Values (to Compare with Actual Value) | A set of numeric column(s) whose results predict the model. For example, if you are using this to evaluate several different linear regressions, the predicted values for each of the regressions is selected here. |
| Output Type |
|
| Output Schema | The schema for the output table or view. |
| Output Table | Specify the table path and name where the output of the results is generated. By default, this is a unique table name based on your user ID, workflow ID, and operator. |
| Drop If Exists | Specifies whether to overwrite an existing table.
|
Output
Visual Output
A table of metrics about each of the predicted columns.

Data Output
None. This is a terminal operator.