This procedure describes how to add the Logistics Regression stage to a workflow in Flow Designer. Logistics Regression is a Machine Learning stage.
To create your model, you must first complete the Model Properties settings. The Basic Options and Advanced Options settings provide sufficient default settings to complete a job, but you can change those settings to meet your needs. After you run your job a limited version of the resulting model appears on the Model Output tab. The complete output is available in the Machine Learning Model Management tool.
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In the Stages panel, scroll to Machine Learning, and drag the Logistics Regression stage onto the canvas.
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Connect the stage to other stages.
The input stage must be the data source that contains the principal components for your model. An output stage is not required but you may connect one if you wish to capture your output independent of the Machine Learning Model Management tool.
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Double-click the Logistics Regression stage to open Logistic Regression Options: Logistics Regression.
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On the Model Properties tab, configure the model name, number of principal components, and the input fields to be included in the analysis.
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On the Basic Options tab, configure to use all factor level, to score input data, the transform, and how to handle missing data.
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On the Advanced Options tab, configure whether to ignore constant fields, the PCA method, and convergence criteria.
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On the Model Output tab, view the metrics you are using to assess the fitted model.
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Click Apply to save your changes.