rminer v1.4.6

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Data Mining Classification and Regression Methods

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.

Functions in rminer

Name Description
mgraph Mining graph function
imputation Missing data imputation (e.g. substitution by value or hotdeck method).
crossvaldata Computes k-fold cross validation for rminer models.
lforecast Compute long term forecasts.
CasesSeries Create a training set (data.frame) from a time series using a sliding window.
Importance Measure input importance (including sensitivity analysis) given a supervised data mining model.
holdout Computes indexes for holdout data split into training and test sets.
delevels Reduce, replace or transform levels of a data.frame or factor variable (useful for preprocessing datasets).
fit Fit a supervised data mining model (classification or regression) model
mining Powerful function that trains and tests a particular fit model under several runs and a given validation method
sa_fri1 Synthetic regression and classification datasets for measuring input importance of supervised learning models
rminer-internal Internal rminer Functions
predict.fit predict method for fit objects (rminer)
savemining Load/save into a file the result of a fit (model) or mining functions.
mparheuristic Function that returns a list of searching (hyper)parameters for a particular model (classification or regression) or for a multiple list of models (automl or ensembles).
mmetric Compute classification or regression error metrics.
sin1reg sin1 regression dataset
vecplot VEC plot function (to use in conjunction with Importance function).
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Details

Type Package
Date 2020-08-14
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

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