# 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). No Results!