dowhy
causalgraph
| dowhy | causalgraph | |
|---|---|---|
| 8 | 1 | |
| 6,781 | 41 | |
| 1.7% | - | |
| 8.8 | 4.1 | |
| 2 days ago | 5 months ago | |
| Python | Python | |
| MIT License | MIT License |
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dowhy
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Causality for Machine Learning
I'm a fan of the Do Why library out of Microsoft. Even as a novice in the field of causal modeling it can get you up and running by estimating the causal graph based on your data. https://github.com/py-why/dowhy
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Acceptable data formats for Predictive Stepwise Logistic Regression
considering how well understood the generating process is, causal analysis could potentially be very powerful here and would model the "not every possible combination of variables is represented" component extremely naturally. https://github.com/py-why/dowhy
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Do you use any specific framework when it comes to causal inference?
The Do-why package could be useful.
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Causal Explanations Considered Harmful: On the logical fallacy of causal projection
Here's one from Microsoft! https://github.com/py-why/dowhy
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[Q] What are some of the most useful topics/classes in philosophy for Statistics?
Before those discussions, it's good to understand the very basics of the topic so you 1) demonstrate momentum to the prof, and 2) have the basis for a meaningful discussion. For causal reasoning, you can check out the Pearl book Causal inference in statistics, a primer, which is short and readable. Definitely check out the Do Why python package which has good tutorials and videos.
- [R] DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models
- DoWhy is a Python library for causal inference
causalgraph
What are some alternatives?
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
CleverCSV - CleverCSV is a Python package for handling messy CSV files. It provides a drop-in replacement for the builtin CSV module with improved dialect detection, and comes with a handy command line application for working with CSV files.
looper - A resource list for causality in statistics, data science and physics
audio-plot-lib - This library provides graph sonification functions and has been developed for a project named "Data science and machine learning resources for screen reader users". Please refer to the project page for more details.
causal-learn - Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
sematic - An open-source ML pipeline development platform
CausalPy - A Python package for causal inference in quasi-experimental settings
OSDT - Optimal Sparse Decision Trees
Causality
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
pyphi - A toolbox for integrated information theory.
SAP-HANA-AutoML - Python Automated Machine Learning library for tabular data.