使用这些数据集，我们可以得到工作项目和它们的结构。
Using these data sets, we can get the work items and their structures.
由于数据集不是对称的，我们可以清楚地排除正态分布模型不是一个合适的选择。
As the dataset is not in a symmetrical shape, we can clearly rule out that a normal distribution model would not be a suitable choice.
问题是，对于许多想要设计系统来应对这些挑战的研究人员来说，实验所需的大量数据集根本不存在。
The trouble is, for many of the researchers who'd like to design systems to address these challenges, massive datasets for experimentation just don't exist.
他们使用的数据集不包括经济数据，所以研究人员转而研究2013至2016年幸福感的下降是否与经济指标有关。
The dataset they used did not include economic data, so instead the researchers looked at whether the 2013-16 wellbeing decline was tracking economic indicators.
“最终的人脸识别算法应该能在一个数据集里处理数十亿人的数据。”研究人员写道。
"An ultimate face recognition algorithm should perform with billions of people in a dataset," the researchers wrote.
对数据集的分布进行建模。
数据集变得难以处理。
其他数据集需要指定。
您的数据集有多大？
但是不生成多维数据集。
选择两个用于合并成虚拟数据集的数据集。
Select the two cubes to be aggregated to form the virtual cube.
您可以从可用数据集列表中选择任意两个数据集。
数据集是BIRT从数据源中获得数据集的结果。
Data sets are result sets of data that BIRT retrieves from the data source.
它自动根据数据集的属性或特征对数据集进行分组。
It automatically groups datasets according to their properties or features.
这仅影响虚拟数据集，而不影响包含该维度的数据集。
This only affects the virtual cube, and not the cube that contains the dimension.
对于虚拟数据集，维度安全性继承自它的两个数据集。
For a virtual cube, the dimensional security is inherited from its two cubes.
虚拟数据集将根据合并运算符合并来自子数据集的结果。
The results are aggregated by the virtual cube according to the merge operator.
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