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Survey of emerging patterns

机译:新兴模式调查

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摘要

Emerging patterns (EPs) which found in 1999 has been proven as strong discriminator which strongly describe significant between 2 datasets. As strong discriminator, EPs will be interested to be used, applied and mixed in many algorithms for finding patterns in many different datasets particularly for text datasets. Using EPs algorithm in Database Management Systems (DBMS) such as MySQL, SQLServer and etc will be interested as well and need to be explored. The differences between 2 datasets literally discriminate knowledge between those datasets which represent with growthrate number as justification of EPs. Moreover, confidence of EPs can be measured in order to secure of finding EPs where confidence will have 100% as maximum score. Since the discrimination is not only between 2 datasets then EPs algorithms have been extended to discriminate between more than 2 datasets which recognized as EPs classification and there are many EPs classification algorithms including Jumping EPs classification as well.
机译:1999年发现的新兴模式(EPs)已被证明是强大的判别器,可以强烈描述两个数据集之间的显着性。作为强鉴别符,EP将有兴趣在许多算法中使用,应用和混合,以在许多不同的数据集中找到模式,尤其是对于文本数据集。在数据库管理系统(DBMS)(例如MySQL,SQLServer等)中使用EPs算法也会引起人们的兴趣,需要进行探索。 2个数据集之间的差异从字面上区分了这些数据集之间的知识,这些知识用增长速度表示为EP的证明。此外,可以测量EP的置信度,以确保找到置信度为最大分数为100%的EP。由于不仅在2个数据集之间进行区分,因此EPs算法已被扩展为可以识别2个以上的EPs分类数据集,并且存在许多EPs分类算法,包括Jumping EPs分类。

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