The Score tool determines the quality of a model's predictions. Use the Score tool to evaluate a model and create an assessment column, known as a score, which estimates the accuracy of the values predicted by the model.
This tool uses the R programming language. Go to Options > Download Predictive Tools to install R and the packages used by the R Tool.
The Score tool can evaluate models from a number of locations:
The Score tool can be configured for models accessed by a standard workflow or for models accessed using the In-DB suite.
The Score tool requires two inputs:
Connect these inputs to the Score tool input to begin configuration.
The Score tool can use a data stream from a predictive model, even if it was estimated using a RevoScaleR function. The Score tool can only use an XDF metadata stream if the input to the modeling tool was from either an XDF Output Tool or XDF Input Tool and the model was estimated using a RevoScaleR function.
Models estimated by Oracle R Enterprise using an In-DB predictive tool connected to an Oracle data source cannot be used to score a standard Alteryx data stream, although models estimated with a standard Alteryx data stream can be used to score Oracle data sources.
The adjustments made through this option are only valid if the target is a binary categorical variable.
If using an ORE-created model, the original estimation table must exist in the database to calculate confidence intervals.
The Score tool supports Oracle, Microsoft SQL Server 2016, and Teradata in-database processing. See In-Database Overview for more information about in-database support and tools.
To access the In-DB version of the Score tool:
See Predictive Analytics for more information about predictive in-database support.
The Score tool requires two inputs:
Connect these inputs to the Score tool input to begin configuration.
The Score tool can use a data stream from a predictive model, even if it was estimated using a RevoScaleR function. The Score tool can only use an XDF metadata stream if the input to the modeling tool was from either an XDF Output Tool or XDF Input Tool and the model was estimated using a RevoScaleR function.
Models estimated by ORE using an In-DB predictive tool connected to an Oracle data source cannot be used to score a standard Alteryx data stream, although models estimated with a standard Alteryx data stream can be used to score Oracle data sources.
No other special characters are allowed, and R is case sensitive.
The adjustments made through this option are only valid if the target is a binary categorical variable.
If using an ORE-created model, the original estimation table must exist in the database to calculate confidence intervals.
The output includes the original data streams with the predicted values of the model.
In the case of a model that uses a categorical target, a predicted probability for each level of the target variable is provided in a field name comprised of the user-provided prefix and the suffix of the field that corresponds to the possible level of the target variable.
Promote is a platform for deploying, managing, and scaling predictive models. Alteryx can connect to the Promote platform to access stored models and score against them.
Establish an Alteryx Promote Connection.
Alteryx Promote Connection: A drop-down list used to select from saved Promote connections.
Add Connection: An option to add to the list of available Promote connections. The Promote connection manager operates independently of workflows.
If you are unsure if you have access to the Promote feature or need assistance finding your required credentials, contact your local administrator or support@alteryx.com.
A list of the models you have access to is generated. Scroll through the list or use the search function to find the model you want to score and select the model path.
Selected Model
Once a model path is selected, information regarding the model populates.
Verify that the model is available for data processing and select Done.
The Configuration Summary provides a summary of the Credentials used and the Model Summary of the selected model.
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