Slovaks, Hungarians and missing data.
斯洛伐克人，匈牙利人和缺失的数据。
是否有缺失的数据？
Missing data were obtained from authors.
失去的数据从作者们获得。
How will default or missing data be standardized?
默认的或缺失的数据如何标准化？
Develop extraction code to obtain the missing data elements.
开发抽取代码以获取丢失的数据元素。
We requested missing data from the authors of the primary study.
我们向原研究作者征询遗漏的资料。
Thirdly, record and manage the missing data with proper statistical methods.
注意记录并用适当的方法处理缺失的数据。
The first step is to add the missing data to the registration form itself (see Listing 1).
第一步，在注册表单中添加缺少的数据，如清单1 所示。
Gnuplot lets you specify a character string to mean a missing data point. For example.
Gnuplot允许您指定字符串，用于表示缺少的数据点。
Your customer should fix missing data in their data source, but they might ask for help.
您的客户应在其数据源中修正丢失的数据，但他们可能会寻求帮助。
This gives an XML query language additional degrees of freedom for dealing with missing data.
这给了XML查询语言更多自由度来处理丢失的数据。
Objective: To explore the results of different methods for managing multivariate missing data.
目的：探讨多变量缺失数据的不同处理方法对结果的影响。
If there is any missing data or dirty data, can your customer correct this in the data sources?
如果有丢失数据或脏(dirty)数据，您的客户是否可以在数据源中进行纠正呢？
Unfortunately, the way a data point with missing data is handled depends on the using specification.
不幸的是，处理缺少数据的数据点的方法取决于using说明。
This method is suitable not only to the complete sample case but also to the general missing data cases.
这种方法既适合于全样本场合又适合于一般缺失数据场合。
For one thing, missing data is not explicitly indicated, but is simply marked by an absent line and time stamp.
一方面，没有显式地标明丢失的数据，而只是通过不存在的行和时间戳进行了简单的标记。
However, if the Ignore missing data attribute of a business process is set, these exceptions are suppressed.
不过，如果设置了业务流程的Ignoremissing data属性，则会禁止这些异常。
We discuss the statistics inference for bidirectionally ordinal square contingency tables with missing data.
本文讨论的是有缺失数据的双向有序方列联表的统计推断。
When a user is returned to a form to fill in missing data, the website should keep completed fields filled in.
给用户返回表单去补充漏填数据的时候，网站应当保留已填数据域的数据。
Missing data filling and rules extraction in incomplete decision table are two important data mining problems.
不完全信息系统中遗失数据的补充和规则的提取，一直是数据挖掘技术面临的重要问题。
Objective To solve the problem of missing data existing in the household health survey and draw valid inferences.
目的解决居民健康调查数据中存在的数据缺失问题，充分利用所采集到的数据，得出更有效的统计推断。
The missing data were analysed with sample selection model and compared with traditional linear regression model.
应用样本选择模型对模拟数据进行分析，并与传统线性回归模型进行比较。
The algorithm constructs decision tree using an improved ID3 algorithm, and fills the missing data by decision rules.
该算法应用改进的ID 3算法来构造决策树，利用决策规则对缺失值进行补充。
Results: the information loss caused by missing data was recuperated and the quality of integrated assessment was improved.
结果：由缺失数据造成的信息缺失得到了弥补，综合评价结果的质量得到了提高。
In combination single imputation of missing data with multiple imputation, a new missing data imputation—KNNMI is proposed.
综合数据缺失值的单一填补和多重填补方法，提出一种新的信用指标缺失值填补方法—KNNMI。
If the missing data or dirty data cannot be corrected in the customer? S data sources, what business rules will be used to correct the data?
如果无法在客户的数据源中纠正丢失的数据或脏数据，什么业务规则将用于纠正数据呢？
This layer is typically predefined, but can be slightly customized to add missing data definitions, relationships and unique name identifiers.
这一层通常是预定义的，但是可以稍微对其进行客户化，如添加一些缺失的数据定义、关系和唯一命名标识等。
This paper USES the improved K-means (IKM) algorithm to process the missing data and thus improve the precision of the Naive Bayes classifier.
本文利用改进的K -均值算法对缺失数据进行处理，提高了朴素贝叶斯分类的精确度。
Simply indicate where missing data will go, how you think (hypothesize) they will look, and how you will interpret them if your hypothesis is correct.
扼要地标明哪些中央还缺数据，你以为（或揣测）这些数据大约是什么样。假如你的揣测是正确的，你将如何去解释它。
Simply indicate where missing data will go, how you think (hypothesize) they will look, and how you will interpret them if your hypothesis is correct.
扼要地标明哪些中央还缺数据，你以为（或揣测）这些数据大约是什么样。假如你的揣测是正确的，你将如何去解释它。
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