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MADBayes is a Python library about Bayesian Networks.

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MADLab MADBayes

MADBayes is a Python library about Bayesian Networks.

Introduction

How to Install

Contents

Legend

  • empty - Not implemented
  • ✔️ - Already implemented
  • ❌ - Non-existent

Structural Properties

Name Python C/C++
Independence Map
U-Separation
D-Separation
Markov Blanket
Equivalence Classes
Topological Ordering

Types of Bayesian Networks

Name Python C/C++
Discrete Networks ✔️
Gaussian Networks
CLG Networks
Mixed Networks

Classifiers

Name Python C/C++
Naive Bayes
Tree-Augmented Naive Bayes

Exact Inference

Type Name Python C/C++
Exact Variable Elimination
Junction Tree ✔️
Approximate Prior Sampling
Rejection Sampling
Likelihood Weighting Sampling
Monte Carlo Chain Sampling

Structural Learning

Type Name Python C/C++
Costraint-based Inductive Causation
Peter & Clark
Grow-Shrink
Incremental Association
Max-Min Parents & Children
Hiton-PC
Score-based Hill-Climbing ✔️
Greedy Equivalent Search
Tabu Search
Genetic Algorithms
Simulated Annealing
Hybrid Sparse Candidate Algorithm
MMHC

Structure Score

Name Python C/C++
Bayesian Information Criterion (BIC)
Akaike’s Information Criterion (AIC)
Bayesian Dirichlet Equivalent Uniform (BDeu)
Bayesian Dirichlet Sparse (BDs) ✔️
Bayesian Gaussian equivalent (BGe)

Missing Data

Name Python C/C++
Expectation-Maximisation ✔️
Structural EM ✔️
Data Augmentation
Bootstrap Aggregation

Causal Models - Effects of Interventions

Name Python C/C++
Interventions
Adjustement Formula
Backdoor Criterion
Front-Door Criterion
Causal Infrence in Linear Systems

Causal Models - Counterfactuals

Name Python C/C++
Counterfactuals
Probabilistic Counterfactuals
Counterfactuals in Linear Systems