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All gene alignments were then concatenated into one large partitioned data set (∼5 kb).
(a) Randomly partition data into V subsets with equal sizes.
Cluster analysis partitions data into significant or useful groups (clusters).
This pre-processing includes partitioning the data into chunks and compressing them.
Because of the volume of data, we used blocking techniques to partition the data into independent clusters and then applied our algorithms on each cluster.
We partitioned the data into two sets, sequence data and gap data.
Because of the small sample size, we could not partition the data into discovery and validation.
Specifically, we partitioned the data into 10 non-overlapping, balanced subsets of cases (outer folds).
For ML analyses, the concatenated data matrix was partitioned into data blocks to account for heterogeneity among sites and to select the most appropriate partitioning scheme and models.
By effectively categorizing and partitioning the data, the big data conundrum has turned into a massive opportunity for the company, and it has also made that data much more secure.
Either set may work for partitioning the test data into symptomatic/asymptomatic subjects.
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