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Hello,
I'm doing causal inference using the virtual twins method (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3880775/). The literature on this and similar method focuses on categorical treatments…
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I have some recommended edits for the [Lift Test Calibration](https://www.pymc-marketing.io/en/stable/notebooks/mmm/mmm_lift_test.html) notebook.
## 1. Under the 'Requirements' section we have
>…
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```
OS Architecture:
```
Operating System: Ubuntu 20.04.4 LTS
Kernel: Linux 5.15.0-53-generic
Architecture: x86-64
```
With a DataFrame of size `(rows, columns) = (9000, 102)`, the `fit` …
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The idea behind a random forest is that, by averaging predictions from many trees, we can do better than any single tree alone could. However, in some instances (e.g., for visualization), it would be …
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Hey there, I have read your awesome work, and have a questions about using it into real data.
Do I need to spicify the relation between the cluster before discovery? I mean if I have a dataset has …
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In terms of functionality, the mid-term end goal is to achieve an offering of ML algorithms and pre-processing routines comparable to what is currently available in Python's [`scikit-learn`](https://s…
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# Problem
When we use the ordinary classification models provided by sklearn, we get poor results because metalearners call the `predict` methods that return 0 or 1.
It would be because metalear…
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Hi,
This is more of a question concerning the _grf_ module rather than an issue. We tried to use _grf.CausalForest_ to estimate the heterogeneous causal effect with multiple treatments. In our case…
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Hi,
I really enjoyed your blog post about HTEs and tried to replicate the results. However, i can't seem to converge on your coefficients after running the R code:
```
> # get top 1/2 of preds
>…
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In the Forest Learners Basic Example notebook, the nuisance estimators are preselected from the full X, T, and Y data before CausalForestDML, etc are fit. How does that interfere with the cross-fittin…