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Mining of Data through various Soft Computing Techniques

机译:通过各种软计算技术挖掘数据

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we experience a daily reality such that we can be overpowered with data; in this manner it has turned out to be progressively critical to separate pertinent data from the unstable measure of information for. Information Mining is the iterative and intuitive procedure of finding substantial, novel, valuable, and justifiable examples or models in gigantic databases. Information Mining implies looking for important data in extensive volumes of information, utilizing investigation and examination, via programmed or self-loader implies, of expansive amounts of information so as to find significant examples and standards. . Soft Computing (SC) alludes to methods of figuring in which accuracy is exchanged for tractability, heartiness and simplicity of usage. For the most part, SC encompasses the technologies of fuzzy logic, genetic algorithms, and neural networks, and it has emerged as an effective tool for dealing with data mining, control, modeling, and decision problems in complex systems. This is a review of the role of various soft-computing tools for different data mining tasks.
机译:我们经历了日常现实,以便我们可以通过数据来压倒;以这种方式,已经证明是从不稳定的信息的不稳定度量分离相关数据。信息挖掘是在巨大数据库中找到实质性,新颖,有价值和合理的例子或模型的迭代和直观的程序。信息挖掘意味着在广泛的信息中寻找重要数据,利用调查和检查,通过编程或自我装载者意味着广泛的信息,以便找到重要的示例和标准。 。软化计算(SC)提及到图解的方法,以便为术而易于易于进行准确性,充分的用途和简单性。在大多数情况下,SC包括模糊逻辑,遗传算法和神经网络的技术,它成为处理复杂系统中的数据挖掘,控制,建模和决策问题的有效工具。这是对不同数据挖掘任务的各种软计算工具的作用的审查。

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