Scikit-survival

This release adds *sksurv.linear_model.CoxnetSurvivalAnalysis* which implements an efficient algorithm to fit Cox's proportional hazards model with LASSO, ridge, and elastic net penalty. Moreover, it includes support for Windows with Python 3.5 and later by making the cvxopt package optional.

This release adds `predict_survival_function` and `predict_cumulative_hazard_function` to `sksurv.linear_model.CoxPHSurvivalAnalysis`, which return the survival function and cumulative hazard function using Breslow's estimator.

Moreover, it fixes a build error on Windows (3) and adds the `sksurv.preprocessing.OneHotEncoder` class, which can be used in a [scikit-learn pipeline](http://scikit-learn.org/dev/modules/generated/sklearn.pipeline.Pipeline.html).

This release adds support for Python 3.6, and pandas 0.19 and 0.20.