Web Application and API for Association Rule Learning and Classification
EasyMiner (EasyMiner/R) is an open source web-based visual interface and REST API for association rule learning built on top of the arules package in R. The system also features implementation of the Classification Based on Associations (CBA) algorithm, which can be used for building classification models from association rules as well as for rule pruning, which addresses the common problem of too many discovered rules. EasyMiner/R also offers an experimental REST-based Prediction API. Unique to EasyMiner is interactive interface that allows to easily define a pattern for rules that you are looking for in your dataset. EasyMiner processes attribute-value data, rather than data in the transaction format.
November 3-4, 2016. EasyMiner Cloud will be presented at WIKT & DataZnalosti by Václav Zeman at Smolenice in Slovakia. Forthcoming
October 4, 2016. Tomáš Kliegr will present EasyMiner at IEEE Days at the University of the West Bohemia. Forthcoming
September 20, 2016. EasyMiner now supports larger datasets with Spark/Hadoop. Just select "Unlimited" as the backend. Note that cloud processing implies additional overhead, this option is thus recommended only if the data cannot be analyzed by the existing open source R backend.
September 11, 2016.
Paper on the new EasyMiner backend accepted for the WIKT/DaZ 2016
June 29, 2016. Tomáš Kliegr presented EasyMiner at CRP13Plus seminar at the Czech Technical University.
December 11, 2015. Jaroslav Kuchař published the first version of the rCBA package powering EasyMiner's pruning and classification in the CRAN repository