Learning Decision Rules from Data Streams
Joao Gama and Petr Kosina
Decision rules, which can provide good interpretability and flexibility for data mining tasks, have received very little attention in the stream mining community so far. In this work we introduce a new algorithm to learn rule sets, designed for open-ended data streams. The proposed algorithm is able to continuously learn compact ordered and unordered rule sets. The experimental evaluation shows competitive results in comparison with VFDT and C4.5rules.