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Methods.py

Methods.py

 
 

README.md

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dependencies.txt

dependencies.txt

 
 

graph.png

graph.png

 
 

main.py

main.py

 
 

scores.csv

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utilsGraph.py

utilsGraph.py

 
 

utilsNetwork.py

utilsNetwork.py

 
 

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Inference-in-Bayesian-networks-4-different-methods

Conditional probability tables for each node in the graph are given. Graph The task is to evaluate the conditional distribution P(I|h-) using 4 different methods:

1. Elimination Method
2. Sampling with Rejection
3. Weigthed Likelihood method
4. Gibbs Sampling

RESULTS

Scores

Evaluated probability is P(i-|h-), P(i+|h-) is just 1-P(i-|h-)

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This repository contains implementation of 4 different methods for inference in Bayesian-networks. Nothing is hard coded.

github.com/Artificial-Intelligence-kosta/Inference-in-Bayesian-networks-4-different-methods

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bayesian-network bayesian-inference graphnetwork montecarlomethod

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