缺失值的英文

• mi ing value
• mi ingvalues
• missing data
• missing values

• "缺失"英文翻译    hiatus; deficiency; deletion
• "值"英文翻译    price; value
• "替换缺失值" 英文翻译 :    replace missing values
• "缺失值的替代" 英文翻译 :    replace missing values
• "极失值" 英文翻译 :    deep out of the money
• "漏失值" 英文翻译 :    missing value
• "遗失值" 英文翻译 :    missing values
• "缺失" 英文翻译 :    hiatus; deficiency; [遗传学] deletion
• "价外；失值（期权）" 英文翻译 :    out-of-the-money
• "合计总损失值" 英文翻译 :    gross arrived damaged value
• "失值（期权）来源：考试大" 英文翻译 :    out-of-the-money
• "鼻缺失" 英文翻译 :    absence of nose
• "道缺失" 英文翻译 :    trace misssing
• "钙缺失" 英文翻译 :    calciprivia
• "喉缺失" 英文翻译 :    absence of larynx
• "碱缺失" 英文翻译 :    base deficit (bd)
• "缺失；洼地" 英文翻译 :    lacuna
• "缺失法" 英文翻译 :    deletion method
• "缺失环" 英文翻译 :    deficiency loop; deletion loop
• "缺失率" 英文翻译 :    miss rate
• "缺失体" 英文翻译 :    deletant
• "缺失位" 英文翻译 :    bit missing; bit, missing
• "缺失相" 英文翻译 :    a ent phase; absent phase
• "肾缺失" 英文翻译 :    absence of kidney; anephrogenesis
• "水缺失" 英文翻译 :    deprivation of water

• 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
• 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。
• As an effective measure , bayesian network model is good at dealing with hide variables and absent values . we focus on devising the bayesian network learning algorithm in order to establish an accurate prediction model
  同时,发现贝叶斯网络作为一种有效的网络构建模型,具有好的统计性和处理隐变量以及缺失值的优越性。
• ( 4 ) the theory and methods of wavelet analysis are introduced to the observation data analysis for dam safety , and the methods for detecting outliers , abstracting trend component , and denoising and detecting missing data by use of wavelet is developed . examples show that the methods are effective
  （ 4 ）将小波分析理论及方法引入大坝安全监测资料分析中，提出了利用小波分析检测异常值、提取趋势分量、降低噪声、检测缺失值的方法，通过实例验证了小波分析方法的有效性。
• After a brief description of concepts involved in the paper , such as rough set theory and the indiscernibility relation , the methods of how to preprocess the loss value of data and how to discrete the data are discussed . the algorithms of attribute < wp = 6 > reduction and value reduction in rough set theory are researched in depth , and then the ordinary reduction algorithms are given . the improved algorithms based on discernibility matrix and decision matrix are put forward
  论文在对所涉及的粗糙集理论以及不可分辨关系等概念进行了简要的阐述后，接着对数据缺失值如何进行预处理以及如何进行数据的离散化处理等方法进行了探讨，然后展开了对粗糙集理论中属性约简以及值约简等算法更进一步的研究，给出了常规约简算法，并在此基础上提出了基于可辨识矩阵以及决策矩阵的改进算法，结果表明算法具有更高的约简效果。
• To the incomplete information systems , the dissertation suggests a new method to impute the null values . the method is based on the extending model of rough sets and fully considers the consistence of data and dependency of attributes . this method can not only avoid deleting those entities including null values , but also avoid redundant extension of the incomplete information system
  对于不完全信息系统，本文利用粗糙集扩展模型，在充分考虑数合肥工业大学博士论文摘要据相容性和属性依赖性的情况下，对缺失值进行了有效的估算，既防止了删除含有空值的对象，使系统缺少典型性，又防止出现过多的、扩展的完全系统。