Remove deprecated 'mode' parameter from sklearn.manifold.spectral_embedding
Remove deprecated 'class_weight' parameter from RidgeClassifierCV.fit
use more interesting range for C in logistic l1 l2 example.

Before this change, output is (http://scikit-learn.org/dev/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html#example-linear-model-plot-logistic-l1-l2-sparsity-py):
C=10
Sparsity with L1 penalty: 6.25%
score with L1 penalty: 0.9104
Sparsity with L2 penalty: 4.69%
score with L2 penalty: 0.9093
C=100
Sparsity with L1 penalty: 6.25%
score with L1 penalty: 0.9098
Sparsity with L2 penalty: 4.69%
score with L2 penalty: 0.9098
C=1000
Sparsity with L1 penalty: 4.69%
score with L1 penalty: 0.9098
Sparsity with L2 penalty: 4.69%
score with L2 penalty: 0.9098

With this change, output is:
C=100.00
Sparsity with L1 penalty: 6.25%
score with L1 penalty: 0.9110
Sparsity with L2 penalty: 4.69%
score with L2 penalty: 0.9098
C=1.00
Sparsity with L1 penalty: 9.38%
score with L1 penalty: 0.9104
Sparsity with L2 penalty: 4.69%
score with L2 penalty: 0.9093
C=0.01
Sparsity with L1 penalty: 85.94%
score with L1 penalty: 0.8625
Sparsity with L2 penalty: 4.69%
score with L2 penalty: 0.8915
Remove deprecated 'precompute_gram' parameter
Remove deprecated 'copy_Gram', 'copy_Xy' and 'copy_X' parameters
Remove deprecated 'Gram' and 'Xy' parameters from OrthogonalMatchingPursuit.fit
Add related project to website.
FIX DBSCAN input validation
Removed 'Gram' and 'Xy' parameters were still in test_omp.py
Remove deprecated 'score_func' and 'loss_func' parameters from sklearn.metrics.scorer.check_scoring. Amend the code in all the other places they were used.
Remove 'copy_X', 'copy_Gram' and 'copy_Xy' documentation since these parameters have been removed
Merge pull request #3412 from brentp/logistic_l1_l2_ex

[MRG] use more interesting range for C in logistic l1 l2 example.
Merge pull request #3411 from lesteve/scheduled-removal-from-0.15

[MRG] Remove deprecated parameters whose removal was scheduled for 0.15
MAINT faster test_weight_boosting
TST speedup test_spectral_biclustering
TST faster check_transformer_pickle by fixing n_iter
TST speedup test_permutation_score

Also remove a warning with fbeta score that had non enought samples of
a specific class by chance.
TST remove joblib tests from sklearn
Tidy up by removing unnecessary local variables
Merge pull request #3414 from lesteve/scheduled-removal-from-0.15

[MRG] Tackle remaining comments in #3411