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34 lines
1.2 KiB
Markdown
34 lines
1.2 KiB
Markdown
**Instructions**
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- After executing those R scripts, an edw_cdr SQL table will be created.
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- Run the code in telcoChurn-operationalize.sql
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- Run the code in telcoChurn-main.sql
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**Description**
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- telcoChurn-main.sql - Use this T-SQL script to try out the telco customer churn example.
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- telcoChurn-operationalize.sql - T-SQL scripts to create the stored procedures used in this example.
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The database consists of the following tables
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- **cdr\_models** - Contains the serialized R models that are used for predicting customer churn
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- **edw\_cdr**- Base Call Detail Records (CDR)
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- **edw\_cdr\_train**- Training data
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- **edw\_cdr\_test** - Testing data
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- **edw\_cdr\_pred** - Predicted results
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and the following stored procedures
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- **generate_cdr_rx_forest** - Train decision forest model with the rxDForest algorithm in RevoScaleR library
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- **predict_cdr_rx_forest** - Predict customer churn using the trained model
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- **model_evaluate** - Generate model performance metrics: Accuracy, Precision, Recall, F-score
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- **model_roccurve** - Generate ROC curve
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- **pie** - Create a pie chart to visualize the proportion of predicted customer churn
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- **stackedbar** - Create a stacked bar chart to visualize the model confusion matrix
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