xiyanghu / OSDTLinks
Optimal Sparse Decision Trees
☆105Updated 2 years ago
Alternatives and similar repositories for OSDT
Users that are interested in OSDT are comparing it to the libraries listed below
Sorting:
- Generalized Optimal Sparse Decision Trees☆66Updated last year
- Born-Again Tree Ensembles: Transforms a random forest into a single, minimal-size, tree with exactly the same prediction function in the …☆66Updated 2 years ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Learning Certifiably Optimal Rule Lists☆175Updated 3 years ago
- A Python package for building Bayesian models with TensorFlow or PyTorch☆175Updated 3 years ago
- A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …☆63Updated 3 years ago
- A toolbox for fair and explainable machine learning☆55Updated last year
- An automated machine learning tool aimed to facilitate AutoML research.☆99Updated 11 months ago
- A Python package for unwrapping ReLU DNNs☆70Updated last year
- This is the implementation of Sparse Projection Oblique Randomer Forest☆99Updated last year
- An extension of CatBoost to probabilistic modelling☆147Updated last year
- An algorithm for learning optimal decision trees, with Python interface☆67Updated 2 years ago
- simple customizable risk scores in python☆141Updated 2 years ago
- ☆100Updated last week
- Surrogate Assisted Feature Extraction☆37Updated 4 years ago
- Multi-Objective Counterfactuals☆42Updated 3 years ago
- 💊 Comparing causality methods in a fair and just way.☆140Updated 5 years ago
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 3 years ago
- python tools to check recourse in linear classification☆78Updated 4 years ago
- Python Meta-Feature Extractor package.☆133Updated last week
- Public home of pycorels, the python binding to CORELS☆80Updated 5 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 8 months ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆61Updated last month
- The stream-learn is an open-source Python library for difficult data stream analysis.☆63Updated 2 months ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 3 years ago
- Causal Graphical Models in Python☆246Updated 2 years ago
- Probabilistic Gradient Boosting Machines☆156Updated last year
- Learn Pyro through the M5 forecasting competition☆86Updated 5 years ago
- Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…☆59Updated 5 years ago