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03. Data Mining

Server Course: Basic Customer Segmentation - Part 3: Data Mining

- Train a k-means model with k=4
- Denormalize the data by exporting input data with clusters and cluster centers
- Document your workflow using annotations and node labels

Activity: Data Mining Activity I- Train a k-means model with k=4- Denormalize the data by exporting input datawith clusters and cluster centers- Document your workflow using annotations andnode labels Activity II- Reset the workflow and make it executable from the firstJoiner node- Create a copy of the wf and rename it as follows:01_Basic_Customer_Segmentation_Use_Case_YourInitials- Upload the Workflow to KNIME Server to the directory:Server Course_My wf Activity III- Schedule a workflow execution (5 mins later). Do not reset the workflow before execution andcheck “Notify upon completion” by adding your email address in the “Standard Job Options” tab- Access to the WebPortal from the Client and execute the workflow from within the WebPortal. Checkthe report that you have created- Make some changes to the workflow (for instance create 5 clusters instead of 4)“01_Basic_Customer_Segmentation_Use_Case_YourInitials” and upload it to KNIME Server in thedirectory “Server Course_My wf”. Create a snapshot of the workflow and check the created snapshotwith the Server History view- Download the created snapshot in the LOCAL Workspace- Use the WorkDiff feature to compare the downloaded workflow with the latest workflow uploaded input datain [0,1]CitiesLongitudeLatitudeContract DataCalls DataChurn -> StringNode 206Node 208Node 209 Joiner Joiner Normalizer (PMML) Table Reader File Reader Excel Reader (XLS)(deprecated) Number To String k-Means Denormalizer (PMML) Denormalizer (PMML) Activity: Data Mining Activity I- Train a k-means model with k=4- Denormalize the data by exporting input datawith clusters and cluster centers- Document your workflow using annotations andnode labels Activity II- Reset the workflow and make it executable from the firstJoiner node- Create a copy of the wf and rename it as follows:01_Basic_Customer_Segmentation_Use_Case_YourInitials- Upload the Workflow to KNIME Server to the directory:Server Course_My wf Activity III- Schedule a workflow execution (5 mins later). Do not reset the workflow before execution andcheck “Notify upon completion” by adding your email address in the “Standard Job Options” tab- Access to the WebPortal from the Client and execute the workflow from within the WebPortal. Checkthe report that you have created- Make some changes to the workflow (for instance create 5 clusters instead of 4)“01_Basic_Customer_Segmentation_Use_Case_YourInitials” and upload it to KNIME Server in thedirectory “Server Course_My wf”. Create a snapshot of the workflow and check the created snapshotwith the Server History view- Download the created snapshot in the LOCAL Workspace- Use the WorkDiff feature to compare the downloaded workflow with the latest workflow uploaded input datain [0,1]CitiesLongitudeLatitudeContract DataCalls DataChurn -> StringNode 206Node 208Node 209 Joiner Joiner Normalizer (PMML) Table Reader File Reader Excel Reader (XLS)(deprecated) Number To String k-Means Denormalizer (PMML) Denormalizer (PMML)

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

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On NodePit since: 2020-06-08
Last update: 2026-01-13
Created with KNIME version: v4.1.2

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