missing value造句
例句与造句
- Represents a missing value in the
信息中的缺少值。 - Nulls are used in a database to indicate an unknown or missing value
Null用于在数据库中指示未知或缺少的值。 - Missing value estimation for microarray expression data based on weighted regression
基因表达缺失值的加权回归估计算法 - Study on processing method of missing values in personalized recommendation systems
个性化推荐系统中遗漏值处理方法的研究 - Or you might use the nil attribute defined in xml schemas to indicate a missing value
或者使用xml模式中定义的nil值来表示忽略的值。 - It's difficult to find missing value in a sentence. 用missing value造句挺难的
- Gets a value indicating whether the column contains non - existent or missing values
获取一个值，该值指示列中是否包含不存在的或缺少的值。 - Gets a value indicating whether the column contains nonexistent or missing values
获取一个值，用以表示列中是否包含不存在的或已丢失的值。 - Gets a value that indicates whether the column contains non - existent or missing values
获取一个值，该值指示列中是否包含不存在的或缺少的值。 - Gets a value that indicates whether the column contains nonexistent or missing values
获取一个值，该值指示列中是否包含不存在的或已丢失的值。 - Filling missing values , smoothing noise data and removing inconsistent data are all adopted to gain high quality data
通过补全缺失数据、平滑噪声数据、消除不一致数据等技术，得到高质量的数据。 - This approach deduces the missing value which makes the best of all information in time zone of missing point
建立前向灰预测和后向灰预测模型，充分利用缺失值时区窗口内的全部信息对其进行推理。 - The fuzzy lookup transformation performs data cleaning tasks such as standardizing data , correcting data , and providing missing values
模糊查找转换执行数据清理任务，例如标准化数据、更正数据以及提供丢失的值。 - The seasonal kendall test overcomes a number of problems that can commonly skew the results of long - term studies , such as non - normal data , missing values , seasonality and serial dependence where data is dependent on other data
这种方法可克服多种分析长期性数据所出现的问题，例如不正常数据数值缺失季节变化和数据相依某类数据依赖其他数据等因素。 - Firstly , influence factors of generalization of neural network are presented in this thesis , in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability , a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes , training epochs , initial weights , and so on ; secondly , through establishing integrating neural network and introducing data fusion technique , the integrality and precision of acquired knowledge is greatly improved . then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement , knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system , by completing missing value data and eliminating unnecessary attributes , discretization of continuous attribute , reducing redundancy , extracting rules in this thesis . finally , rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge , in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement , and rnn can improve the speed and quality of knowledge acquirement greatly
本文首先讨论了影响神经网络的泛化能力的因素,提出了一种新的结构自适应神经网络学习算法,在新方法中,采用了遗传算法对神经网络的结构参数(隐层节点数、训练精度、初始权值)进行优化,大大提高了神经网络的泛化能力和知识动态获取自适应能力;其次,构造集成神经网络,引入数据融合算法,实现了基于集成神经网络的融合诊断,有效地提高了知识获取的全面性、完善性及精度;然后,针对知识获取过程中所存在的不确定性、不完备性等问题,探讨了运用粗糙集理论的知识获取方法,通过缺损数据补齐、连续数据的离散、冲突消除、冗余信息约简、知识规则抽取等一系列的算法实现了智能诊断的知识规则获取;最后,将粗糙集理论与神经网络相结合,研究了粗糙集-神经网络的知识获取方法。 - This paper also studies in detail the problem of building concept lattice , and two efficient algorithms are developed . moreover , several extended model of concept lattice are presented to handle the problems in data processing , such as the missing value and the structured domain of attribute
此外，本文还对概念格的快速生成算法进行了深入的研究，提出了一些高效的算法，文章的最后提出了几种概念格扩展模型，处理了数据中可能出现的缺值和结构化属性值域的问题。
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