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Enabling Decision Tree Classification in Database Systems through Pre-computation

机译:通过预计算在数据库系统中启用决策树分类

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摘要

Integration of data mining in database systems is an open topic of research. The DBMS's power of dealing with lots of data and maintaining data integrity adds to the motivation of integrating it with data mining. We propose a method to integrate decision tree classification to do the required pre-computations and store it in database objects for later use. These pre-computed values get updated with the introduction of new data or change in the existing data for classification. Decision tree classification can readily make use of these pre-computed values to build classification models. Our approach is based on the column database to use it effectively for feature oriented calculations. This comparatively improves performance if classification is deemed to be performed on a high dimensional data.
机译:在数据库系统中集成数据挖掘是一个开放的研究主题。 DBMS处理大量数据和维护数据完整性的能力增加了将其与数据挖掘集成的动机。我们提出了一种集成决策树分类以进行所需的预计算并将其存储在数据库对象中以供以后使用的方法。这些预先计算的值会随着引入新数据或更改现有数据进行分类而更新。决策树分类可以很容易地利用这些预先计算的值来建立分类模型。我们的方法基于列数据库,以有效地将其用于面向特征的计算。如果认为要对高维数据执行分类,则可以相对提高性能。

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