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quantitative attribute中文是什么意思

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用"quantitative attribute"造句"quantitative attribute"怎么读"quantitative attribute" in a sentence

中文翻译手机手机版

  • 量的属性
  • 品质属性
  • 数量属性

例句与用法

  • Attributes reduct , mining classification rules , and discretizing values of quantitative attributes are three fields in mining classification rules
    属性约简、分类规则提取、数量属性离散化是分类规则挖掘的三个方面。
  • ( 3 ) the evolutionary computation - based algorithm for discretizing values of quantitative attributes , whose advantage is that it can finding the best cuts of a quantitative attribute
    ( 3 )根据进化计算的极强鲁棒性及寻优能力,提出了基于进化计算的数量型属性离散化算法?进化c均值算法。
  • How to handle these attributes affects the mining results and the efficiency . the dissertation proposes the methods of changing the quantitative attributes into bool attributes , so that many algorithms can be used , based on enhanced fcm and the genetic method
    ( 2 )在分布式挖掘过程中,分布式数据库中存在着大量的数量属性,这些数量属性的处理好坏,直接影响着关联规则的挖掘效果和效率。
  • And also this taxonomy gives the quantitative attributes in more sides on finer layers and emphasizes the influences of vulnerabilities on the confidentiality , authentication and availability of systems so that it can provide abundant information for vulnerability description and assessment
    此外,也提供了弱点多侧面细层次上的量化属性,并且突出了弱点对系统机密性、可鉴别性和可用性等安全属性的影响,为量化的弱点描述、评估提供了丰富的信息支持。
  • However , in practical applications , considering cost in constructing the networks or management in networks , users prefer staring networks to net networks which do not meet their requirements . the dissertation proposes the c - dma algorithm to solve this problem , based on fdm and cd . experimental results show that the performance of the c - dma is available and extendable . ( 2 ) in the process of mining association rules , the quantitative attributes exit in databases
    但是,在实际的网络应用环境中,用户基于成本和管理等方面的需要,使用的网络结构往往是星型结构的,所以cd算法和fdm算法在网络结构和实际的网络结构不相适应,本文在cd算法及fdm算法的基础上提出以中心结点结构的分布式关联规则挖掘算法,并且从算法分析和仿真试验两个方面证明了算法的有效性和可扩展性。
  • For the data with quantitative attribute , several unsupervised discretization methods of continuous features are discussed . three simple boolean discretization methods ( equal width , equal frequency and cluster ) and fuzzy discretization are simulated based on a real population statistical database
    随后针对数据库中的模拟量属性,分析了非监督定量属性离散化的几种方法,在一个统计数据库基础上仿真研究了分别基于等宽、等频和聚类的布尔型分段离散化方法和模糊离散化方法。
  • In the process of data mining , there exists a sharp boundary problem if using intervals to deal with quantitative attributes , so we introduce fuzzy sets to solve this problem , and experiment results approve the feasibility of using fuzzy association rules and fuzzy frequency episodes to detect anomalies
    在数据挖掘过程中,由于利用间隔来处理数值属性容易产生尖锐的边界问题,我们引入模糊集的概念到数据挖掘算法来解决这个问题,给出了具体的算法,并通过实验证实了利用模糊关联规则和模糊频繁序列检测异常的可行性。
  • Because the existing vulnerability taxonomies at large lack support for the quantitative assessment and uncovering the vulnerability correlations , this dissertation proposes a vulnerability taxonomy for mining the correlations with multidimensional quantitative attributes , gives the corresponding mining algorithm and an experiment is given to validate the effectivity of the algorithm
    由于已有的弱点分类法普遍缺乏对量化评估以及对揭示弱点关联特性的支持,为此,本文提出了一种支持关联性挖掘的多维量化属性弱点分类法,给出了相应的挖掘算法,并以实验验证了该算法的有效性。
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