Data Mining Classification and Regression Methods

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Documentation for package ‘rminer’ version 1.4.9

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CasesSeries Create a training set (data.frame) from a time series using a sliding window.
centralpar Powerful function that trains and tests a particular fit model under several runs and a given validation method
crossvaldata Computes k-fold cross validation for rminer models.
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
holdout Computes indexes for holdout data split into training and test sets.
Importance Measure input importance (including sensitivity analysis) given a supervised data mining model.
imputation Missing data imputation (e.g. substitution by value or hotdeck method).
lforecast Compute long term forecasts.
loadmining Load/save into a file the result of a fit (model) or mining functions.
loadmodel Load/save into a file the result of a fit (model) or mining functions.
metrics Compute classification or regression error metrics.
mgraph Mining graph function
mining Powerful function that trains and tests a particular fit model under several runs and a given validation method
mmetric Compute classification or regression error metrics.
model-class Fit a supervised data mining model (classification or regression) model
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).
predict-method predict method for fit objects (rminer)
predict-methods predict method for fit objects (rminer)
predict.fit predict method for fit objects (rminer)
savemining Load/save into a file the result of a fit (model) or mining functions.
savemodel Load/save into a file the result of a fit (model) or mining functions.
sa_fri1 Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_int2 Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_int2_3c Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_int2_8p Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_psin Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_ssin Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_ssin_2 Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_ssin_n2p Synthetic regression and classification datasets for measuring input importance of supervised learning models
sa_tree Synthetic regression and classification datasets for measuring input importance of supervised learning models
sin1reg sin1 regression dataset
vecplot VEC plot function (to use in conjunction with Importance function).