rminer: Data Mining Classification and Regression Methods
Version 1.4.2

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: 1.4.2 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.

Getting started

Package details

AuthorPaulo Cortez [aut, cre]
Date of publication2016-09-02 22:48:18
MaintainerPaulo Cortez <pcortez@dsi.uminho.pt>
URL http://cran.r-project.org/package=rminer http://www3.dsi.uminho.pt/pcortez/rminer.html
Package repositoryView on CRAN
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rminer documentation built on May 29, 2017, 10:05 a.m.