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Optimization and improvement of data mining algorithm based on efficient incremental kernel fuzzy clustering for large data

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The arrival of the big data era in the new century has made the traditional data mining algorithms unable to meet the requirements of big data mining in accuracy and… Click to show full abstract

The arrival of the big data era in the new century has made the traditional data mining algorithms unable to meet the requirements of big data mining in accuracy and efficiency. Therefore, a data mining algorithm based on efficient incremental kernel fuzzy clustering for big data was optimized—in this paper. First of all, the methods of big data mining and fuzzy clustering technique for data mining were summarized. Then, the data mining algorithm based on the incremental kernel fuzzy clustering was optimized. Finally, the method was validated by comparing with the stKFCM algorithm. The verification results showed that the improved algorithm was superior in performance and accuracy, but only a slight gap in running time.

Keywords: fuzzy clustering; incremental kernel; data mining; mining; algorithm based; mining algorithm

Journal Title: Cluster Computing
Year Published: 2018

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