Titlebook: Advanced Data Mining and Applications; 14th International C Guojun Gan,Bohan Li,Shuliang Wang Conference proceedings 2018 Springer Nature S

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Berichte zur Resistenzmonitoringstudie 2009k is applied to classification of SDC vulnerability. Finally, compared with the model based on SVM and Decision Tree, the experiment results show that the average accuracy of LSTM in classification of SDC vulnerability is 11.73% higher than SVM, and 10.74% higher than Decision Tree.

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0302-9743 ions. The papers were organized in topical sections named: Data Mining Foundations; Big Data; Text and Multimedia Mining; Miscellaneous Topics..978-3-030-05089-4978-3-030-05090-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Berichte zur Lebensmittelsicherheit 2013science. Mining this massive data is a very challenging task because conventional data mining algorithms are unable to scale effectively with massive time series data. Moreover, applying a global classification approach to a highly similar and noisy data will hinder the classification performance. T

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Berichte zur Lebensmittelsicherheit 2013cated to transform the high-dimensional data into one-dimensional distance data. Multiple Gamma models are built on distance data, which are fitted with the expectation-maximization algorithm. The best-fitted model is selected with the second-order Akaike information criterion. We estimate the candi

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https://doi.org/10.1007/978-3-319-27906-0time-series dataframe. The algorithm purposed to use a set of “first-partial derivative potential value” given from HASTA in the multiple dataframes as the input to the autoregressive integrated moving average (ARIMA) under preliminary parameters. The ARIMA model could perform the pre-labeling task

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