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- missing data imputation 缺失值填充
- 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。
- 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。
- Insufficient disk space to insert missing data attribute. 磁盘空间不足以插入丢失的数据属性。
- This paper presents a HMM Local Optimal state Path-based Data Imputation (LOPDI) algorithm. 该文提出了基于隐马尔可夫模型局部最优状态路径的数据重建(LOPDI)算法。
- missing data imputing 缺失数据填充
- 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。
- 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 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。
- 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。
- In order to evaluate, optimize and monitor the industrial process more effectively, missing data usually needs to be reconstructed. 为了更好的对工业过程进行分析评估、优化及监控，往往需要重构遗失的数据。
- 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。
- Investigators concluded that proper handling of missing data, including treatment failures, is necessary when comparing bariatric procedures. 研究者结论表示，适当的处理漏失资料，包括治疗失败，在比较减重手术时是必要的；
