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The project builds a Bayesian Network using pressure sensor data to detect pipe leaks, employing probabilistic reasoning to determine the likelihood of leaks based on sensor readings. It involves loading dataset, defining network structure, calculating CPDs, adding them to model, and using Variable Elimination algorithm for inference
The objective of this study is to explore the impact of the structure of a Bayesian Network on its overall run-time, potential unwanted bias, and accuracy in performing a classification task. A credit card default dataset was utilised to construct six networks with varying structures and to learn their conditional probability distributions.
FAIRK_M3 contains the mini-project developed for the Module 3 of the course "Fundamentals of Artificial Intelligence and Knowledge Representation" in the university of Bologna.
This project is developed in Python and it proposes the development of a Bayesan Network to infer the probabilities of serious floods in the territory of the Italian region Veneto.
Project involves the application of bayesian inference using python pgmpy library. The python script modelled the bayes net and obtained some probabilities based on the model.
Using bayesian networks to aid the design of a drone. Mini project developed as part of the course of Fundamentals of AI and Knowledge Representation of University of Bologna.