compboost 0.1.1

23.01.2019
Style: Change . to _, e.g. change n.knots to n_knots, to be more consistent with C++ syntax.
23.01.2019
There is now a new Response class to be more versatile for given tasks.
14.12.2018
To track the out of bag risk is now easy controllable through a argument oob.fraction. The paths of inbag vs. out of bag risk can be plotted with plotInbagVsOobRisk()
28.11.2018
It is now possible to directly access the logger data with getLoggerData() and to calculate and plot feature importance with calculateFeatureImportance() and plotFeatureImportance().
27.11.2018
Fix bug in the spline base-learner for out of range values.
09.11.2018
Adding a new optimizer OptimizerCoordinateDescentLineSearch which conducts line search after each iteration.
09.11.2018
Improve trace of the training process by passing logger identifier directly to C++.

compboost 0.1.0

Initial release

19.07.2018
Compboost now uses sparse matrices for splines to reduce memory load.
29.06.2018
Compboost API is almost ready to use.
14.06.2018
Update naming GreedyOptimizer -> OptimizerCoordinateDescent and small typos.
30.03.2018
Compboost is now ready to do binary classification by using the BernoulliLoss.
29.03.2018
Upload C++ documentation created by doxygen.
28.03.2018
P-Splines are now available as base-learner. Additionally the Polynomial and P-Spline learner are speed up using a more general data structure which stores the inverse once and reuse it for every iteration.
21.03.2018
New data structure with independent source and target.
01.03.2018
Compboost should now run stable and without memory leaks.
07.02.2018
Naming of the C++ classes. Those are matching the R classes now.
29.01.2018
Update naming to a more consistent scheme.
26.01.2018
Add printer for the classes.
22.01.2018
Add inbag and out of bag logger.
21.01.2018
New structure for factories and base-learner. The function InstantiateData is now member of the factory, not the base-learner. This should also speed up the algorithm, since we don't have to check whether data is instantiated or not. We can do that once within the constructor. Additionally, it should be more clear now what the member does since there is no hacky base-learner helper necessary to instantiate the data.