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In order to improve the performance of machine learning in big data, online multiple kernel learning algorithms are proposed in this paper. First, a supervised online multiple kernel learning algorithm for big data (SOMK_bd) is proposed to reduce the computational workload during kernel modification. In SOMK_bd, the traditional kernel learning algorithm is improved and kernel integration is only carried out in the constructed kernel subset. Next, an unsupervised online multiple kernel learningdoi:10.12928/telkomnika.v14i2.2751 fatcat:nwqxuspzundtxm3rofq75e7kdy