Values can be propagated across linked records for missing or conflicting data so that a common representation of name or tax ID will be present on all linked records.
对于缺失或有冲突的数据，值可以在链接的记录之间传播，以便在所有链接的记录中提供名称或taxID的通用表示。
The way of effective data complement for a data set with missing values was analyzed so as to reflect more objectively internal relationship among data in data set.
分析了在含有遗失值的数据集上如何进行有效的数据填补，以便更客观地反映数据集中数据所隐含的内在联系。
Conclusion The multiple-imputation method was the best technique to handle with the missing values in the schistosomiasis surveillance data.
结论多重填充技术较为适合处理该资料中缺失比例较少的缺失值。
Filling missing values, smoothing noise data and removing inconsistent data were all adopted to get 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。
You control the data collection process, so you can ensure data quality, minimize the number of missing values, and assess the reliability of your instruments.
你控制着数据收集过程，因此您可以确保数据质量，将丢失的数量价值减到最小化，评估仪器的可靠性。
Objective to compare the three imputation methods of missing values and provide scientific basis for the best imputation methods of missing values for the schistosomiasis surveillance data in China.
目的以全国血吸虫病疫情监测资料为数据来源，比较不同缺失值处理方法对模拟缺失值的处理结果，为确定适用于处理该资料缺失值的方法提供依据。
Missing values contained in microarray data will affect subsequent analysis.
微阵列数据中的缺失值会对随后的数据分析造成影响。
To rectify the problem, missing data has been replaced by default values.
为改正该问题，缺少的数据已由默认值所代替。
Missing values in traffic flow data should be imputed because complete data are needed for space-time data mining.
交通流量的时空数据挖掘需要完整的数据，因此必须处理交通流量数据中的缺失值。
The data with missing values in two-factor experiment with randomized block design is the unbalanced data with unequal replications of level combination of two factors.
有缺失数据两因素随机区组试验资料是两因素水平组合重复数不等的非平衡资料。
Conclusion mi and MIANALYZE procedures provide a valid strategy for handling data set with missing values.
结论多重填补与多重填补分析为处理存在缺失数据的资料提供了有效的策略。
A imputation method based on Mahalanobis distance was proposed to estimate missing values in the gene expression data.
提出了一种基于马氏距离的填充算法来估计基因表达数据集中的缺失数据。
When we analyse seasonal series of hospital data, there are missing values and outliers. It is difficulty for forecasting.
医院季节性时间序列分析中，会出现缺失数据和异常值，这就影响了预测预报。
When we analyse seasonal series of hospital data, there are missing values and outliers. It is difficulty for forecasting.
医院季节性时间序列分析中，会出现缺失数据和异常值，这就影响了预测预报。
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