Which supervised learning technique(s) do you lean towards as your "go to" solution?
Why are the density plots for Bayesian results off-center?
When, how, and why?
How would you decide on the number of clusters to use?
Find a good rule of thumb to decide the number of hidden layers in a neural net.
Investigate other blind signal separation techniques, such as ICA.
Use other methods, such as
poisson, in the
rpartfunction (especially if you have a natural occurring dataset).