Bugfixes in gaussian_process subpackage

Hi list,

It's been a while... ;-)

I've been told the `random_start` feature of the GaussianProcess estimator was making it worse rather than making it better.
It was indeed due to a bad handling of sign in the randomly restarted maximization of the reduced likelihood function (implemented as the minimization of the opposite reduced likelihood function with `fmin_cobyla`).

While running GP tests and examples, I spotted another mistake in the `gp_diabetes_dataset` example which appeared when the optimized `theta` value stored in the estimator was made "private" by renaming it to `theta_`.

Cheers!