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
Download H20 jar with version h2o-3.30.1.2, Link for download h2o-3.30.1.2.zip
java -jar h2o.jar
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 :
Manual entry in PostgreSQL, mention type as AUTOML .
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"}
Configure Usecase :
Navigate to Forecasting: Here you will see already created usecases.
Click on add button to upload data.
Input unique usecase name and upload test csv data.
Once the file gets uploaded then below details needs to be filled.
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.
Column Mapping Detail
Fill the details for each column type and mention columns used for word2vector analysis.
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.
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.
KPI Creation:
Refer below sample KPI creation window .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.