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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