October 2015
Beginner to intermediate
168 pages
4h 11m
English
Content preview from Learning Bayesian Models with R
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Bayesian treatment of neural networks
To set the neural network learning in a Bayesian context, consider the error function 
for the regression case. It can be treated as a Gaussian noise term for observing the given dataset conditioned on the weights w. This is precisely the likelihood function that can be written as follows:
Here, 
is the variance of the noise term given by and represents a probabilistic model. The regularization term can be considered ...
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