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- missing data imputing 缺失数据填充
- Consequently, one does not have to deal with missing data such as removing observations or imputing data points. 因此,不必处理那些缺失的数据,例如:观察的改动或者是数据的输入点造成的数据缺失。
- Missing data were imputed conservatively. 漏失数据适当处理。
- Missing data were imputed conseratiely. 漏失数据适当处理。
- Imputing missing data in Clinics dataset by NBI model has an obvious improvement on the classification accuracy, especially for the accuracies of middle stay patients and long stay patients. NBI模型对提高病人住院持续时间(Length of Stay, LOS)的预测准确率有显著作用,尤其是中期和长期的预测准确率有明显的提高。
- Insufficient disk space to insert missing data attribute. 磁盘空间不足以插入丢失的数据属性。
- The computer data security exists in software and hardware ,exists in the links of data imputing, processing, exporting, conserving, transmission. 安全问题存在于电脑硬件及软件之中,也存在于数据输入、加工、存储、传输、转存等环节上。
- missing data imputation 缺失值填充
- Further,the paper proposes the detailed program operation process,especially dwells on the two key modules including the data identification module and data imputing module. 其次,给出了详细的总体程序工作流程,并且针对其中的两个核心模块给出了具体的工作流程。
- First,the paper conducts the program flow design,including the data retrieving module,the data identification module,the data imputing module,the data storage module and the data output module. 首先进行程序流程设计,包括数据读取模块、数据识别模块、数据修正模块、数据存储模块和数据输出模块五部分,各模块间相互联系,按照数据流的方向结合在一起按顺序使用。
- Tail log backups capture the tail of the log even if the database is offline, damaged, or missing data files. 尾日志备份可捕获日志尾部,即使数据库离线、损坏或缺少数据文件。
- 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。
- When you have restored all the available database and log files, you are still missing data. 在已经还原了所有可用的数据库和日志文件时,仍然丢失了一些数据。
- Some methods for processing missing data by applying data mining are introduced. 将数据挖掘用于处理卫星数据中的空缺数据,给出了数据挖掘中对空缺数据处理的方法;
- They also identify the missing data pieces to the sender so it can retransmit the missing data. 传送端也可以利用序号判别遗失的资料区块,才能重新传送遗失的资料。
- Missing data in the income variables is familiar and is hard to treat in econometric analysis. 在经济计量分析中收入变量的缺失值是一个普遍而又较难处理的问题。
- Experimental results show that it significantly outperforms the missing data and acoustic backing-off techniques. 实验结果表明,所提识别方法的性能显著优于丢失数据技术和声学后退技术。
- Any missing data could cause a corrupt communication that is either incomplete or unreadable. 任何缺失的数据可能会导致既不完整也无法读取的损毁原意的沟通。
- It is proposed that using multiple imputation by chained equations deals with missing data in the income variables. 本文提出利用基于链式方程的多重插补方法来处理收入变量的缺失值问题。
- Conclusion: Multilevel models can efficiently analyze longitudinal data with hierarchical structure and missing data. 结论:多水平模型可以有效地分析具有层次结构的、含有缺失值的纵向数据资料。