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In order to ensure that we are able to give our customers a reflection of both past and future state - it is imperative that we add forecasting capabilities to our product. We will use H20 as the AI/ML platform for forecasting capabilities and it would be integrated to Insights for training and model deployment.

Pre-Requisite:  

  • Start the H2O jar locally using below command

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    • java -jar h2o.jar 

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    • By default H2O starts in port: 54321.

    • Mention below configuration inside server-config.json.

    • "mlConfiguration": {"h2oEndpoint": "http://localhost:54321"}.

  • DB Table Entry: INSIGHTS_WORKFLOW_TYPE  :

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    • Manual entry in PostgreSQL, mention type as AUTOML .

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    • API Used:- /PlatformService/insights/workflow/saveWorkflowTask  
      Workflow task Json
      {"description":"H2O_AutoML_Execute","mqChannel":"WORKFLOW.TASK.AUTOML.EXCECUTION","componentName":"com.cognizant.devops.automl.task.core.AutoMLSubscriber","dependency":-1,"workflowType":"AUTOML"}

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Configure Usecase :

  • Navigate to Forecasting: Here you will see already created usecases.

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  • Click on add button to upload data.

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    • Input unique usecase name and upload test csv data.

    • Once the file gets uploaded then below details needs to be filled.

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  • Split Ratio and Target Column

    • Split Ratio: Select split percentage as Training and Test.

    • Maximum Models to run: Specify the number which indicates maximum algorithms to run against training data.

    • Response Column: select response column as prediction column.

    • Prediction Type: Select prediction type as either Classification or Regression.

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  • Column Mapping Detail

    • Fill the details for each column type and mention columns used for word2vector analysis.

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  • Click on the save button to save the usecase.

  • The usecase is save as ONETIME workflow and is picked up by Immediate Workflow Scheduler.


Executing Usecase:

  • To execute the usecase run the workflow engine.

  • Once workflow ran successfully check the status of the workflow as LEADERBOAD_READY as highlighted below.

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  • Select this usecase and click on the Leaderboard button on the Top.

  • Select the best MOJO in the list and Save the MOJO.

  • Once MOJO gets saved the Status is changed to MOJO_DEPLOYED as highlighted below and the usecase would be ready for further use in Report Section.

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    KPI Creation:
    Refer below sample KPI creation window

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  • Category must be selected as PREDICTION.

  • Select the usecase from the list. The list of those usecase available whose status is MOJO_DEPLOYED in Usecase Management Screen.

  • Save the KPI.


 
Report Configuration: 

  • Report configuration steps are same as Report Management so refer Report Configuration Documentation.

  • While creating the report make sure selecting KPI's created at KPI creation step.