slds-lmu / iml_methods_limitationsLinks
Seminar on Limitations of Interpretable Machine Learning Methods
☆57Updated 4 years ago
Alternatives and similar repositories for iml_methods_limitations
Users that are interested in iml_methods_limitations are comparing it to the libraries listed below
Sorting:
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆39Updated 3 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
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- This is the implementation of Sparse Projection Oblique Randomer Forest☆99Updated last year
- An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model☆75Updated 5 years ago
- A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …☆63Updated 3 years ago
- Generalized additive model with pairwise interactions☆66Updated last year
- Python library for Ceteris Paribus Plots (What-if plots)☆24Updated 4 years ago
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- Bayesian or-of-and☆34Updated 3 years ago
- Feature Interaction Interpretability via Interaction Detection☆34Updated 2 years ago
- GAMI-Net: Generalized Additive Models with Structured Interactions☆31Updated 3 years ago
- ☆29Updated 6 years ago
- 💊 Comparing causality methods in a fair and just way.☆139Updated 5 years ago
- Introductory overview of Bayesian inference☆44Updated 6 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆56Updated 2 years ago
- A Python package for building Bayesian models with TensorFlow or PyTorch☆174Updated 2 years ago
- AutoLearn, a domain independent regression-based feature learning algorithm.☆30Updated 5 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆60Updated 4 years ago
- SMOGN: a Pre-processing Approach for Imbalanced Regression - LIDTA2017☆25Updated 7 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆58Updated last year
- Python implementation of R package breakDown☆43Updated last year
- Causing: CAUsal INterpretation using Graphs☆58Updated 3 weeks ago
- An extension of CatBoost to probabilistic modelling☆144Updated last year
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated 2 months ago
- repository for R library "sbrlmod"☆25Updated last year
- Some notes on Causal Inference, with examples in python☆153Updated 5 years ago
- The stream-learn is an open-source Python library for difficult data stream analysis.☆63Updated 3 weeks ago
- scikit-learn gradient-boosting-model interactions☆25Updated 2 years ago
- R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''☆46Updated 4 years ago