add functionality to NearestNeighbors estimators
Roger-Stanimoto -> Rogers-Tanimoto
calculate kernel norm only once
compute kernel norm only once
TST: compare gaussian KDE against scipy version
Change dual splits to single splits in query_dual
Add SVD-based solver to ridge regression.

I added a solver based on the thin SVD of X to compute the ridge
coefficients. This is much more stable than the cholesky decomposition
for singular matrices.

While in the Ridge regression the Gram matrix becomes nonsingular
because of the regularization, I've come across problems when the
regularization parameter is very small. This pull request remedies,
making the algorithm defined and stable even for the border case
alpha=0.

I took the liberty to change the default algorithm of to this one
(when there are no sample weights).
Remove unnecessary code in ridge svd
BUG: solver was not passed to computational method in Ridge object
Use Cholesky solver by default, but use SVD as fallback

when the cholesky fails.
Use ValueError for non-existant solvers
WMinkowskiDistance corrections to error messages and docstring
improvement
Merge pull request #7 from jhale/new_ball_tree

WMinkowskiDistance corrections to error messages and docstring
added first version of out-of-core example
revision round #1 (move to examples/applications, 1 file, auto-download dataset)
Fixed typo in metrics.py
ENH faster unique_labels for big sequences of sequences
Fix L2 regularization order in sgd_fast
DOC explain labels parameter to confusion_matrix
corrected doctests after moving L2 penalty application in SGD