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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Bayesian and Neural Networks
 Hložek, Bohuslav ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This paper introduces Bayesian neural network based on Occams razor. Basic knowledge about neural networks and Bayes rule is summarized in the first part of this paper. Principles of Occams razor and Bayesian neural network are explained. A real case of use is introduced (about predicting landslide). The second part of this paper introduces how to construct Bayesian neural network in Python. Such an application is shown. Typical behaviour of Bayesian neural networks is demonstrated using example data.
Detailed record
Bayesian and Neural Networks
 Hložek, Bohuslav ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This paper introduces Bayesian neural network based on Occams razor. Basic knowledge about neural networks and Bayes rule is summarized in the first part of this paper. Principles of Occams razor and Bayesian neural network are explained. A real case of use is introduced (about predicting landslide). The second part of this paper introduces how to construct Bayesian neural network in Python. Such an application is shown. Typical behaviour of Bayesian neural networks is demonstrated using example data.
Detailed record
Lesk a bída optimálních stromů
 Savický, Petr ; Klaschka, Jan
Optimal classification trees have the smallest error on training data, given the number of leaves. Previous experiments suggest that the generalization properties of the optimal trees might be consistently at least as good as these of the trees grown by classical methods. The result presented in current paper demonstrate, however, that for some classification problems the optimal trees are outperformed by the classical ones.
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