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 - new classification and regression models/algorithms, 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 (improved mmetric function); 1.2 - new input importance methods (improved Importance function); 1.0 - first version.

Akshit Achara, Lars Kotthoff, Hans W. Borchers, Guido Tack
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.

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.
pandoc (>=1.14, needed for the vignette)

Derivative-Free Optimization in R using C++
c(person("Sam", "Watson", email = "S.I.Watson@bham.ac.uk",
role = c("aut")),
person("Yi", "Pan", email = "ypan1988@gmail.com",
role = c("aut", "cre")),
person("Éric", "Thiébaut", role = c("aut")),
person("Mike", "Powell", role = c("aut")))
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>).
Sam Watson [aut],
Yi Pan [aut, cre],
Éric Thiébaut [aut],
Mike Powell [aut]