Titlebook: Discovery Science; 24th International C Carlos Soares,Luis Torgo Conference proceedings 2021 Springer Nature Switzerland AG 2021 applied co

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书目名称Discovery Science影响因子(影响力)




书目名称Discovery Science影响因子(影响力)学科排名




书目名称Discovery Science网络公开度




书目名称Discovery Science网络公开度学科排名




书目名称Discovery Science被引频次




书目名称Discovery Science被引频次学科排名




书目名称Discovery Science年度引用




书目名称Discovery Science年度引用学科排名




书目名称Discovery Science读者反馈




书目名称Discovery Science读者反馈学科排名

cultivated

https://doi.org/10.1007/978-3-030-88942-5applied computing; artificial intelligence; batch learning; classification and regression trees; compute

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978-3-030-88941-8Springer Nature Switzerland AG 2021

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https://doi.org/10.1007/978-3-658-04158-8iased ground-truth of the graders. In this paper, we focus on the automated grading of free-text responses. We formulate the problem as a binary classification problem of two class labels: low- and high-grade. We present a benchmark on four machine learning methods using three experiment protocols o

calumniate

Willensfreiheit, Physik und Hirnforschungare based on heuristics which rely on a set of software metrics and corresponding threshold values. Those techniques and tools suffer from subjectivity issues, discordant results among the tools, and the reliability of the thresholds. To mitigate these problems, we used machine learning to automate

B-cell

https://doi.org/10.1007/978-3-658-04158-8ntegrate multiple HTML tables into a single table for retrieval of information containing in various Web pages. The method is designed by extending tree-structured LSTM, the neural network for tree-structured data, in order to extract information that is both linguistic and structural information of

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Willensfreiheit, Physik und Hirnforschungnce introduces new challenges for both the performance assessment of these models and their predictive modeling. While several performance metrics have been established as baselines in balanced domains, some cannot be applied to the imbalanced case since the use of the majority class in the metric c

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