Drew Herren's repositories
explainability-analysis
Analysis of several techniques for model explainability
semi-supervised-propensity
Code for the paper "Semi Supervised Propensity Score Estimation"
implementations
Implementations of common algorithms / statistical methods for didactic purposes
BartReadingGroup
BART and Posterior Summarization Reading Group at UT Austin
dissertation-experiments
Code for experiments and simulation studies run in my PhD dissertation
oscar-explainability
Model explainability using the OSCAR algorithm
shap-anova-examples
Code examples from the Arxiv release on the relationship between SHAP and functional ANOVA
andrewherren.github.io
Drew Herren's personal webpage
acic2024
Slides and vignettes from the ACIC 2024 BART workshop
arborist-api
API for stochastic tree ensembles using FastAPI for AWS Lamda deployment.
covid-19-excess-deaths-tracker
Source code and data for The Economist's covid-19 excess deaths tracker
covid-19-the-economist-global-excess-deaths-model
The Economist's model to estimate excess deaths to the covid-19 pandemic
EigenDemo
Cross-platform programs that use Eigen (for debugging and performance profiling)
minimalist_tree
Minimalist C++ implementation of decision tree algorithms
possum
POSterior SUMmarization
python-machine-learning-book
The "Python Machine Learning (1st edition)" book code repository and info resource
rethinking
Statistical Rethinking course and book package
scikit-learn
scikit-learn: machine learning in Python
scikit-tree
Flexible library for implementing and experimenting with tree methods, based on the scikit-learn tree codebase
shapley-regression
For calculating Shapley values via linear regression.