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A Survey on Data Classification using Machine Learning TechniquesA Survey on Data Classification using Machine Learning Techniques

机译:使用机器学习技术进行数据分类的调查使用机器学习技术进行数据分类的调查

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Data classification is an essential step in trying to safeguard one of the chief properties of an organization -its information. Data classification engages categorizing information to predefined levels. For every level, organizations must allocate different levels of security controls and restrict the number of employees or persons who can access the information. Data classification would be difficult in large organizations with significant content to estimate and classify. With the assistance of a data classification approach, organizations can recognize and implement proper setting for private access control and also can obtain decision based on the obtained result from data classification. Machine learning techniques are one of the best classification approaches in the recent development. Many techniques are available under the machine learning approaches and the most important objective of machine learning research is to automatically learn toidentify complex patterns and make intelligent decisions based on data. In this paper, data classification using many Machine Learning Techniques has been discussed. This paper focuses on better Machine Learning Techniques which supports data classification are available in the literature.
机译:数据分类是试图保护组织的主要特性之一即信息的重要步骤。数据分类可将信息分类到预定义的级别。对于每个级别,组织必须分配不同级别的安全控制,并限制可以访问信息的员工或人员的数量。在具有大量内容要进行估计和分类的大型组织中,数据分类将很困难。借助数据分类方法,组织可以识别和实施私有访问控制的正确设置,还可以基于从数据分类中获得的结果来获取决策。机器学习技术是最近发展中最好的分类方法之一。机器学习方法下有许多技术可用,机器学习研究的最重要目标是自动学习以识别复杂的模式并基于数据做出明智的决策。在本文中,已经讨论了使用许多机器学习技术进行数据分类。本文着重于更好的机器学习技术,该技术支持文献中的数据分类。

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