adaXT - Fast Adaptable and Extendable Trees for Research
adaXT is a Python module for tree-based machine learning algorithms that is fast, adaptable and extendable. It is intended to
provide a simple way of constructing specialized tree-based algorithms but also contains several default algorithms
for classification, regression, conditional quantile estimation and gradient estimation.
- R code for “StabilizedRegression” available on CRAN. Source
and bug report on github.
- R code for “CausalKinetiX” available on CRAN. Source
and bug report on github.
- R code for “dHSIC” available on CRAN. Source
and bug report on
github.
- R code for “seqICP” available on
CRAN. Source
and bug report on github.
- Python, R and Matlab code for “coroICA” is available on the project website.
Causality Jupyter Notebooks (in R and Python)
We have created several short self-contained exercises that provide an overview on several selected topics related to
causality. They are available here.