rminer (1.4.3)

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Data Mining Classification and Regression Methods.

https://cran.r-project.org/package=rminer http://www3.dsi.uminho.pt/pcortez/rminer.html

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: 1.4.3 new metrics (e.g., macro precision, explained variance), new least squares support vector machine 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/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.

Maintainer: Paulo Cortez
Author(s): Paulo Cortez [aut, cre]

License: GPL-2

Uses: adabag, Cubist, e1071, glmnet, kernlab, kknn, lattice, MASS, mda, nnet, party, plotrix, pls, randomForest, rpart, xgboost

Released about 1 month ago.

8 previous versions



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