Facilitates the use of data mining algorithms in classification and regression (including time series forecasting) tasks by presenting a short and coherent set of functions. Versions: 1.4.6 / 1.4.5 / 1.4.4 new automated machine learning (AutoML) and ensembles, via improved fit(), mining() and mparheuristic() functions, and new categorical preprocessing, via improved delevels() function; 1.4.3 new metrics (e.g., macro precision, explained variance), new "lssvm" model and improved mparheuristic() function; 1.4.2 new "NMAE" metric, "xgboost" and "cv.glmnet" models (16 classification and 18 regression models); 1.4.1 new tutorial and more robust version; 1.4 - new classification and regression models, with a total of 14 classification and 15 regression methods, including: Decision Trees, Neural Networks, Support Vector Machines, Random Forests, Bagging and Boosting; 1.3 and 1.3.1 - new classification and regression metrics; 1.2 - new input importance methods via improved Importance() function; 1.0 - first version.

Constraint optimization, or constraint programming, is the name given to identifying
  feasible solutions out of a very large set of candidates, where the problem can be modeled in terms 
  of arbitrary constraints. 'MiniZinc' is a free and open-source constraint modeling language. 
  Constraint satisfaction and discrete optimization problems can be formulated in a high-level 
  modeling language. Models are compiled into an intermediate representation that is understood by a
  wide range of solvers. 'MiniZinc' itself provides several solvers, for instance 'GeCode'. R users 
  can use the package to solve constraint programming problems without using 'MiniZinc' directly, 
  modify existing 'MiniZinc' models and also create their own models.

Perform derivative-free optimization algorithms in R using C++.
    A wrapper interface is provided to call C function of the 'bobyqa' implementation
    (See <https://github.com/emmt/Algorithms/tree/master/bobyqa>).

Provides header files of 'mio', a cross-platform C++11 header-only 
    library for memory mapped file IO <https://github.com/mandreyel/mio>.