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rminer - A open-source library that facilitates the use of Machine Learning methods in R

This package was used in several Machine Learning / Data Mining applications: intensive care medicine, meat and wine quality assessment, civil engineering, forest fires prediction, modeling student performance, time series forecasting, spam e-mail detection and others. Available at the Comprehensive R Archive Network (CRAN). The rminer package tutorial pdf is available here and the respective code is available here.

Springer Book: Modern Optimization with R (R code, data, ...)

Benchmark of AutoML tools: IJCNN 2021 paper results, data & code

Datasets:

• Automotive Display Anomaly (anomaly detection in industrial process data, binary classification, available at since 2025).

• Cross-source cross-domain sentiment analysis (classification, available at GitHub since 2019).

• Twitter-country-geolocation (classification, available at GitHub since 2019).

• CS Abstracts Dataset (sequential classification, available at GitHub since 2018).

• Online News Popularity (regression/classification, donated to the UCI ML repository in 2015).

• Stock Market Lexicon (with more than 20.000 microblog terms associated with positive or negative scores, available at GitHub, created in  2015).

• Student Performance (regression/classification, donated to the UCI ML repository in 2014).

• Bank Marketing (classification, donated to UCI ML repository in 2014).

• Input importance synthetic datasets (regression and classification, eXplainable Artificial Intelligence - XAI, see this paper: Elsevier or RepositoriUM, created in 2012).

• Internet Traffic Time Series Datasets (time series forecasting, see this paper: Wiley or RepositoriUM; also available at tsdl R package - index 643 to 648, donated in 2012).

• S-Enron corpus (personalized spam e-mail classification, 5 users, "Date:" field should be used to mix the ham 

and spam messages, see this paper: Elsevier or RepositoriUM, created in 2011).

• Wine Quality (regression/classification) donated to the UCI ML repository in 2009).

• Forest Fires (regression, donated to the UCI Machine Learning (ML) repository in 2008).