This application is not supported by InterSystems Corporation. Please be notified that you use it at your own responsibility.
What's new in this version
Customer churn predictor
This application is an example of using IRIS Cloud SQL and integrated ML to solve customer churn problems.
As an example, the application uses a demo dataset of telecommunications company clients from https://www.kaggle.com/datasets/blastchar/telco-customer-churn.
To try the application you can use online demo or run it locally with your own Cloud SQL account.
To start, use the command
> docker-compose up --build
And open http://127.0.0.1:8011/
Open your Cloud Service Portal and create the new Deployment
Go to configuration page in the app and set your deployment credentials
In Cloud Service Portal open "Add and Manage files" and add WA_Fn-UseC_-Telco-Customer-Churn.csv from /data folder
Open "Import files" and import current file to Customers table
Then go to "IntegratedML Tools" and create and train new model with training model name "customer_churn_predictor_tr"
Go to app again, enter customer data and look to result
Tag version: 1.0.0
Released: 2023-04-18 12:12:38
Works withInterSystems IRIS Cloud SQL
GitHub (Link to the GitHub repository)
Tag1, Tag2, Tag3
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Previous value: `Customer churn predictor`
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Previous value: `https://github.com/danoleg/customer-churn-predictor/blob/main/LICENSE`
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