Predictor (Regression)
Overview
Transform-type Snap-
Works in Ultra Tasks
Prerequisites
- The data from upstream Snap must be in tabular format (no nested structure).
Limitations and known issues
None.
Snap views
| View | Description | Examples of upstream and downstream Snaps |
|---|---|---|
| Input | This Snap has at most two input views. Any Snap that generates an unlabeled document. Any Snap that reads and outputs the classification model. | |
| Output | This Snap has at least one and at most one document output views. | File Reader |
| Error |
Error handling is a generic way to handle errors without losing data or failing the Snap execution. You can handle the errors that the Snap might encounter when running the pipeline by choosing one of the following options from the When errors occur list under the Views tab. The available options are:
Learn more about Error handling in Pipelines. |
|
Snap settings
Legend:
- Expression icon (
): JavaScript
syntax to access SnapLogic Expressions to set field values dynamically (if enabled). If
disabled, you can provide a static value. Learn more. - SnapGPT (
): Generates SnapLogic Expressions
based on natural language using SnapGPT. Learn
more. - Suggestion icon (
): Populates a
list of values dynamically based on your Account configuration. - Upload
: Uploads files. Learn more.
| Field / field set | Type | Description |
|---|---|---|
| Label | String |
Required. Specify a unique name for the Snap. Modify this to be more appropriate, especially if more than one of the same Snaps is in the pipeline. Default value: Predictor Regression Example: Regression model |
| Snap execution | Dropdown list | Select one of the three modes in which the Snap executes.
Available options are:
|