// Hint: These classes are intended to be used as base classes. Do not
// simply add your code to these files - instead create a new class
// derived from one of CSizingControlBarXX classes and put there what
// you need. See CMyBar classes in the demo projects for examples.
On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and deta ...
Hibernate: A Developer s Notebook shows you how to use Hibernate to automate persistence: you write natural Java objects and some simple configuration files, and Hibernate automates all the interaction between your objects and the database. You don t even need to know the database is there, and you ...
Here we are at the crossroads once again
Youre telling me youre so confused
You cant make up your mind
Is this meant to be
Youre asking me
Trademark
But only love can say - try again or walk away
But I believe for you and me
The sun will shine one day
So Ill just play my part
And pray you ll have a ...
Without this, the debugger spontaneously fails!
1 - Install mdk315b
2 - Replace the files:
\Keil\ARM\BIN\ARM.DLL with one from mdk305a\Keil\ARM\BIN\ARM.DLL
\Keil\ARM\BIN31\ARM.DLL with one from mdk305a\Keil\ARM\BIN30\ARM.DLL
\Keil\UV3\UV3.DLL with one from mdk305a\Keil\UV3\UV3.DLL (*)
3 - Use ...
This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, N ...
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that n ...
This Two-Category Classifier Using Discriminant Functions to
separeate two classes. The Classifier is designed on classes which
has two feature vectors and other case it has one feature vector.
A technical trading system comprises a set of trading rules that can be used to generate trading signals. In general, a simple trading system has one or two parameters that determine the timing of trading signals. Each rule contained in a trading system is the results of parameterizations.
(Source ...
