Proposed changes

Hi,

This feature adds an option for causal trees to return counterfactual outcomes $\hat{Y}(X|T=0)$, $\hat{Y}(X|T=1)$ along with estimated individual treatment effects.

Details:

• predict() method in CausalTreeRegressor and CausalRandomForestRegressor got flag with_outcomes that enables to return nx3 array of outcomes and treatment effects.
• Usage example was added to causal_trees_with_synthetic_data.ipynb notebook.
• New test for causal trees covers columns check in predict() output

Related issues: #590

Update:

• Dependencies fix: limit numpy version
• Requirements migration to pyproject.toml.

Types of changes

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• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
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• Lint and unit tests pass locally with my changes
• I have added tests that prove my fix is effective or that my feature works
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