syanga / pycit
(Conditional) Independence testing & Markov blanket feature selection using k-NN mutual information and conditional mutual information estimators. Supports continuous, discrete, and mixed data, as well as multiprocessing.
☆27Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for pycit
- pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆65Updated 3 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆59Updated 4 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (Python version)☆19Updated 3 years ago
- [Experimental] Global causal discovery algorithms☆89Updated this week
- CPDAG Estimation using PC-Algorithm☆93Updated 2 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆43Updated 2 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆59Updated 3 months ago
- Makes algorithms/code in Tetrad available in Python via JPype☆61Updated this week
- Example causal datasets with consistent formatting and ground truth☆66Updated last year
- An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.☆64Updated last year
- Code for the paper "Estimating Transfer Entropy via Copula Entropy"☆39Updated last year
- Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…☆54Updated 9 months ago
- Active Bayesian Causal Inference (Neurips'22)☆51Updated 3 months ago
- [Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.☆47Updated this week
- Causal discovery for time series☆90Updated 2 years ago
- ☆17Updated last year
- ☆89Updated last year
- Rule Extraction Methods for Interactive eXplainability☆41Updated 2 years ago
- Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning☆39Updated 9 months ago
- Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge☆23Updated last year
- Python package for (conditional) independence testing and statistical functions related to causality.☆22Updated last month
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 5 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 3 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆57Updated last year
- For calculating Shapley values via linear regression.☆66Updated 3 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆51Updated 3 years ago
- Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…☆98Updated 11 months ago
- Breast cancer prediction using causal Inference☆10Updated 3 years ago
- a Matlab library of computational causal discovery and variable selection algorithms☆18Updated 4 years ago
- Python code of information geometric causal inference☆12Updated 5 years ago