Package: rminer
Type: Package
Title: Data Mining Classification and Regression Methods
Version: 1.4.6
Date: 2020-08-14
Authors@R: c(person("Paulo", "Cortez",role=c("aut","cre"),email="pcortez@dsi.uminho.pt"))
Author: Paulo Cortez [aut, cre]
Maintainer: Paulo Cortez <pcortez@dsi.uminho.pt>
Description: 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.
Imports: methods, plotrix, lattice, nnet, kknn, pls, MASS, mda, rpart,
        randomForest, adabag, party, Cubist, kernlab, e1071, glmnet,
        xgboost
LazyLoad: Yes
License: GPL-2
URL: https://cran.r-project.org/package=rminer
        http://www3.dsi.uminho.pt/pcortez/rminer.html
NeedsCompilation: no
Packaged: 2020-08-28 09:36:37 UTC; root
Repository: CRAN
Date/Publication: 2020-08-28 11:10:02 UTC
Built: R 4.1.0; ; 2021-05-28 10:22:52 UTC; unix
