decision_function forces dense output (in the case of sparse coef_)
ENH sparsify method for L1-reg linear models

Currently implemented on LinearSVC, LR and SGD.
ENH: support float value for max_features
DOC: if float, then max_features is a percentage
ENH: Defer parameter checking of trees
DOC: GBRT max_features
TEST: added test
ENH: use numbers
FIX: numpy integers
Merge branch 'sparse-coef'

Conflicts:
	doc/whats_new.rst
COSMIT callable instead of hasattr __call__
BUG update graph_laplacian to upstream SciPy version

Fixes several bugs and I hope #1698 as well.
DOC rm failing doctest on graph_laplacian
DOC fix text vectorizer docs and add NLTK example

The narrative docs did not correctly describe the working of a custom
analyzer, which will actually skip the built-in preprocessing and
tokenization.
DOC fix broken doctests for feature_extraction.text

This time, I actually did run the doctests, but they succeeded
because I have NLTK installed.
StratifiedKFold: remove pointless copy of labels
DOC add random_state parameter to docs of LogisticRegression and LinearSVC
TST/FIX set random_state in logistic regression tests
TST/FIX always use "almost equal" for floats.
ENH CountVectorizer using arrays instead of lists