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Bayesian Networks Applications
Chaloupka, David ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This master's thesis deals with possible applications of Bayesian networks. The theoretical part is mainly of mathematical nature. At first, we focus on general probability theory and later we move on to the theory of Bayesian networks and discuss approaches to inference and to model learning while providing explanations of pros and cons of these techniques. The practical part focuses on applications that demand learning a Bayesian network, both in terms of network parameters as well as structure. These applications include general benchmarks, usage of Bayesian networks for knowledge discovery regarding the causes of criminality and exploration of the possibility of using a Bayesian network as a spam filter.
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Návrh řešení studeného startu doporučovacího systému
MAŠTALÍŘ, Jakub
The main topic of the bacholor´s thesis is design and implementation of the recommender system´s module in the field of tourism and travelling. In the theoretical part the goal is mapping out an environment of the recommender system, their types and approaches. Furthermore there is described the problem of cold start and the theory of Bayes networks on the basis of which the data for the recommendation will be processed and presented. In the practical part we are programming and testing the recommender module. There is a description of the used technologies and individual functionalities of the recommender system aimed at the acommodation in České Budějovice are dismembered.
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Use of Bayesian Networks in Managerial Practice
Rod, Martin ; Váchová, Lucie (advisor) ; Bína, Vladislav (referee)
The main goal of our bachelor thesis is to create a quantitave model which describes real biogas plant (property of company VOD Kadov) and its troubleshooting. Our created model has broad applications. It can be used as a support tool for managerial decision making either for biogas plant's malfunction or for its improvement. Secondly it plays a major role in quantitative clarification of inner links and processes which takes place inside the biogas plant. This quantification is done by Bayesian statistic approach via Bayesian network and its methods. For modeling purposes we exploit (leak) noisy OR-gate model and various methods for variable discretization. We heavily use company's data for model creation. With our model we simulated the run of biogas plant and its possible malfunctions. We also provided an easy step by step guide how to troubleshoot these malfunctions.
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Bayesian Networks Applications
Chaloupka, David ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This master's thesis deals with possible applications of Bayesian networks. The theoretical part is mainly of mathematical nature. At first, we focus on general probability theory and later we move on to the theory of Bayesian networks and discuss approaches to inference and to model learning while providing explanations of pros and cons of these techniques. The practical part focuses on applications that demand learning a Bayesian network, both in terms of network parameters as well as structure. These applications include general benchmarks, usage of Bayesian networks for knowledge discovery regarding the causes of criminality and exploration of the possibility of using a Bayesian network as a spam filter.
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Aplikace metod strojového učení na dolování znalosti z dat
Kraus, Jan
The diploma thesis deals with the area of data mining applied to large collections of textual data. Specifically the thesis is focused on sentiment analysis based on the user's subjective verbal assessment in natural language. The first part of the diploma thesis introduces the reader to basic terms of machine learning and data mining applied particularly to large textual data collections. Following is the description of textual data preprocessing methods and principles of machine learning algorithms. In the practical part of this thesis there are experiments designed and subsequently executed using the SPSS Modeler tool. The experimental part is focused especially on identification of significant attributes and recongnition of relationships between them. The emphasis is put especially on thorough interpretation of the results obtained.
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