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The Paper: “A Deep Probabilistic Model for Customer Lifetime Value Prediction”
A run through the paper’s neural network architecture and loss function
- Paper Overview
- Deep Dive: Architecture - Output Layer
- Deep Dive: ZILN Loss
Predicting a customer’s lifetime value (LTV) can be quite a challenging task. Wang, Liu and Miao propose using a neural network with a mixture loss to handle the intricacies of churn and lifetime value modelling of new customers.
In this blogpost we’ll take a look at their proposed solution and go through the …