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Lead Scoring Pyspark Batch Inference Pipeline

In this project, we UCI Bank Marketing dataset for lead scoring. Lead classification is used to score leads based on the information we gather. It is different from lead qualification which is used to identify ideal customers. Lead scoring helps sales and marketing team focus their efforts on customers who are most likely to buy.

Model Selection

Model Accuracy Area under ROC Area under PR
Logistic Regression 0.891 0.878 0.488
SVM 0.905 0.933 0.581
Decision Tree 0.916 0.638 0.421
Random Forest 0.913 0.915 0.658
Gradient Boosting Trees 0.919 0.948 0.663

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We perform batch inference on lead scoring task using Pyspark.

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