Online ABC miner: An online rule learning algorithm based on Artificial Bee Colony algorithm
Fehim Köylü · 2017
Data mining is the process of extracting a meaningful information from raw data. Classical data mining algorithms can be used to extract an offline static model for classification problems which has a collected dataset. Unfortunately, Offline algorithms cannot give a solution for nowadays' technologies with streaming data. Streaming algorithms are proposed to deal with data-streams for online learning in the literature. In this paper, a new online classification rule learning algorithm based on a swarm based optimization algorithm, Artificial Bee Colony algorithm, is proposed. Experimental results obtained in this study conducted that the proposed algorithm can be used for data-streams.