This is the Linux app named Causal ML whose latest release can be downloaded as v0.15.5sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS
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Causal ML
DESCRIPTION
Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions on the model form. An important lever to increase ROI in an advertising campaign is to target the ad to the set of customers who will have a favorable response in a given KPI such as engagement or sales. CATE identifies these customers by estimating the effect of the KPI from ad exposure at the individual level from A/B experiments or historical observational data.
Features
- A Python Package for Uplift Modeling and Causal Inference with ML
- Documentation available
- Campaign targeting optimization
- Personalized engagement
- Examples available
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/causal-ml.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
