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pipelinex_causallift's Introduction

PipelineX CausalLift

An example project using PipelineX, Kedro, and CausalLift for Uplift Modeling to find which customers should be targeted and which customers should not for a marketing campaign (treatment).

Pipeline visualized by Kedro-viz

1. Install dependencies

$ pip install pipelinex causallift xgboost kedro mlflow kedro-viz

Note: mlflow and kedro-viz are optional.

2. Clone this repository and run main.py

$ git clone https://github.com/Minyus/pipelinex_causallift.git
$ cd pipelinex_causallift
$ python main.py

Tested environment

  • Python 3.6.8

Simplified Kedro project template

This project was created from the GitHub template repository at https://github.com/Minyus/pipelinex_template

To use for a new project, fork the template repository and hit Use this template button next to Clone or download.

pipelinex_causallift's People

Contributors

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Stargazers

Andres Mariscal avatar avatar Adi Lin avatar Jeff avatar Ramsey avatar

Watchers

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Forkers

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pipelinex_causallift's Issues

ValueError: Input contains NaN, infinity or a value too large for dtype('float64')

Hi, first of all thank you for the great package, it is amazing.
I'm having some problems and would appreciate a lot if you could help.
While running this code I got an error

cl = CausalLift(X0, X1, enable_ipw=True, verbose=3)

[2021-01-14 15:07:57,554|causallift.nodes.estimate_propensity|INFO]

Confusion Matrix for Test:

[2021-01-14 15:07:57,559|kedro.pipeline.node|ERROR] Node estimate_propensity([args,df_00,propensity_model]) -> [df_01] failed with error:
Input contains NaN, infinity or a value too large for dtype('float64').
[2021-01-14 15:07:57,564|kedro.runner.sequential_runner|WARNING] There are 1 nodes that have not run.
You can resume the pipeline run by adding the following argument to your previous command:
ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

There are no such values in my train/test datasets, I think it is somehow related to the propensity score calculation. Can you please help how to resolve?

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