Titlebook: New Frontiers in Mining Complex Patterns; 4th International Wo Michelangelo Ceci,Corrado Loglisci,Zbigniew W. Ras Conference proceedings 20

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Comparison of Tree-Based Methods for Multi-target Regression on Data Streamsly, we apply a local method based on the FIMT-DD algorithm and propose a novel global method, named iSOUP-Tree-MTR. Furthermore, we present an experimental evaluation that is mainly oriented towards exploring the differences between the local and the global approach.

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/n/image/665285.jpg

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https://doi.org/10.1007/978-3-319-39315-5data mining; ensemble methods; knowledge discovery; machine learning; parallel algorithms; classification

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Michelangelo Ceci,Corrado Loglisci,Zbigniew W. RasIncludes supplementary material:

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Frequent Itemsets Mining in Data Streams Using Reconfigurable Hardware approaches for Data Mining cannot be used straightforwardly in data stream scenario. This paper introduces a single-pass hardware-based algorithm for frequent itemsets mining on data streams that uses the top-k frequent 1-itemsets. Experimental results of the hardware implementation of the proposed algorithm are also presented and discussed.