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02_​Deployment_​Workflow_​with_​Manual_​Deployment

Production Workflow with Manual Deployment

This workflow shows a simple example of churn prediction deployment with optimized threshold. This workflow is used for comparison before Integrated Deployment was introduced with KNIME 4.2. You can see how the trained models are manually loaded via Model Reader nodes and the optimized threshold hardcoded via a Rule Engine node.


Area code and churn are converted to String. apply newthresholdread missing value modelread random forest modelNumber To String Random ForestPredictor Missing Value(Apply) Rule Engine Domain Calculator ContainerInput (Row) ContainerOutput (Row) Model Reader Model Reader Column Filter Area code and churn are converted to String. apply newthresholdread missing value modelread random forest modelNumber To String Random ForestPredictor Missing Value(Apply) Rule Engine Domain Calculator ContainerInput (Row) ContainerOutput (Row) Model Reader Model Reader Column Filter

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Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: paolotamag
Created at: 2020-07-03
On NodePit since: 2020-07-17
Last update: 2024-04-17
Created with KNIME version: v4.5.1
Tags: manual deploymentchurn predictionbinary classificationREST API

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