[WIP] Kernel Ridge Regression

Adds an implementation of Kernel Ridge Regression (KRR)

Basic implementation of KRR based on @mblondel's code in lightning. In addition to the lighning code, documentation and an example comparing KRR and SVR is added. The example illustrates the models learned by KRR and SVR:

![plot_kernel_ridge_regression_001](https://cloud.githubusercontent.com/assets/1116263/5330658/9793f8f6-7e03-11e4-93a9-7da2f0634037.png)

Furthermore, it compares the time required for fitting the model and predicting with the model for different sizes of the training set:

![plot_kernel_ridge_regression_002](https://cloud.githubusercontent.com/assets/1116263/5330660/a1b7a4cc-7e03-11e4-8628-3d6cccad921a.png)

We know here that by preprocessing, `alpha` is an `ndarray`. So it would suffice to have `one_alpha = (alpha == alpha[0]).all()`, which would avoid creating a long list of `alpha[0]` which would then have to be converted to an array.