How to use CausalLift?
There are 2 ways:
[Deprecated option] Use
causallift.CausalLift
class interface[Recommended option] Use
causallift.nodes
subpackage withPipelineX
package
[Deprecated option] Use causallift.CausalLift
class interface
Please see the demo code in Google Colab (free cloud CPU/GPU environment):
To run the code, navigate to “Runtime” >> “Run all”.
To download the notebook file, navigate to “File” >> “Download .ipynb”.
Here are the basic steps to use.
from causallift import CausalLift
""" Step 1. """
cl = CausalLift(train_df, test_df, enable_ipw=True)
""" Step 2. """
train_df, test_df = cl.estimate_cate_by_2_models()
""" Step 3. """
estimated_effect_df = cl.estimate_recommendation_impact()
[Recommended option] Use causallift.nodes
subpackage with PipelineX
package
Please see PipelineX package and use PipelineX Causallift example project.