S Learner Uplift Model for Individual Treatment Effect and Customer Segmentation in Python Uplift model using meta-learner s-learner for heterogeneous individual treatment effect (ITE) and marketing customer segmentation

S Learner Uplift Model for Individual Treatment Effect and Customer Segmentation in Python

S-learner is a meta-learner that uses a single machine learning model to estimate the individual level causal treatment effect. In this tutorial, we will talk about: Resources for this post: Let’s get started! Step 1: Install and Import Libraries In step 1, we will install and import the python libraries. Firstly, let’s install causalml for synthetic dataset …

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