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Kernel Association for Classification and Prediction: A Survey

机译:内核分类和预测协会:一项调查

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摘要

Kernel association (KA) in statistical pattern recognition used for classification and prediction have recently emerged in a machine learning and signal processing context. This survey outlines the latest trends and innovations of a kernel framework for big data analysis. KA topics include offline learning, distributed database, online learning, and its prediction. The structural presentation and the comprehensive list of references are geared to provide a useful overview of this evolving field for both specialists and relevant scholars.
机译:最近在机器学习和信号处理环境中出现了用于分类和预测的统计模式识别中的内核关联(KA)。该调查概述了大数据分析内核框架的最新趋势和创新。 KA主题包括离线学习,分布式数据库,在线学习及其预测。结构性介绍和全面的参考文献清单旨在为专家和相关学者提供这一发展领域的有用概述。

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