论文信息 - EasyMiner/R Preview: Towards a Web Interface for Association Rule Learning and Classification in R

EasyMiner/R Preview: Towards a Web Interface for Association Rule Learning and Classification in R

EasyMiner is a web-based visual interface for association rule learning. This paper presents a preview of the next release, which uses the R environment as the data processing backend. EasyMiner/R uses the arules package to learn rules. It uses the Classifications Based on Associations (CBA) algorithm as a classifier and to perform rule pruning. Experimental results show that EasyMiner with the R-based backend is able to handle larger datasets than the previous version.

Vaclav Zeman | Jaroslav Kuchar | Stanislav Vojír | Tomás Kliegr

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