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Below is my code to estimate treatment effects. There is a much wider confidence interval of ATT (i.e., [-200k, 900k]) by Causal Forest DML model, compared to that calculated by linear DML model (i.e,…
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**What is your question?**
Hi,
I have pretrained several Random Forest (RF) models using cuRFC.
I need to iterate through these models to make predictions and add the results to a DataFrame.
Ho…
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I ran the genetic algorithms for 100 generations. Each generation has a population of ~2700. Quick statistic
- Scoring = (initial_score - shuffled_column) score.
- After ~77 generations
…
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### Describe the workflow you want to enable
I am part of the @neurodata team. We are proposing to add a cythonized module that allows for building oblique trees.
Oblique trees, otherwise known …
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Hola! No entiendo muy bien como tiene que ser el bagging en el random forest, y a qué se refiere F, me podrían explicar un poco?
Lo que por ahora entiendo, y que averigüé un poco mas en Wikipedia, …
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Replace these with `from_raw_data`:
1. `plot.confusion_matrix(y_test, y_pred)`
2. `plot.roc(y_test, y_pred)`
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### Is your feature request related to a problem? Please describe.
This feature is related to the problem of customers opting new products and leaving old products
### Describe the solution you'…
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This project involves predicting the duration of NYC taxi trips using various regression models. The notebook includes steps for data exploration, preprocessing, model training, and evaluation.
## …
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**Is your feature request related to a problem? Please describe.**
There's no algorithm for Random Forest implementation for Machine Learning using python.
**Describe the solution you'd like**
Im…
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To improve the MLacc performance, a neural network could be implemented to accept all input variables and predict multiple response variables at the same time. This requires modifying `ML.py` and `tra…