Graduation Year
2017
Date of Submission
4-2017
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
Computer Science
Reader 1
Arthur H. Lee
Rights Information
© 2017 Anant V. Jaitha
Abstract
Bayesian networks are a means to study data. A Bayesian network gives structure to data by creating a graphical system to model the data. It then develops probability distributions over these variables. It explores variables in the problem space and examines the probability distributions related to those variables. It conducts statistical inference over those probability distributions to draw meaning from them. They are good means to explore a large set of data efficiently to make inferences. There are a number of real world applications that already exist and are being actively researched. This paper discusses the theory and applications of Bayesian networks.
Recommended Citation
Jaitha, Anant, "An Introduction to the Theory and Applications of Bayesian Networks" (2017). CMC Senior Theses. 1638.
https://scholarship.claremont.edu/cmc_theses/1638
Included in
Artificial Intelligence and Robotics Commons, Other Computer Sciences Commons, Theory and Algorithms Commons
