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Exact(32)
Subsection 3.5 directly estimates the degree of mismatch between these two datasets using information theoretic measures.
Despite the differences between these two datasets, our models trained on HumanEva dataset obtain a relatively close result as method in [43].
In order to evaluate the relationships between soil fertility and remotely sensed data, partial least-squares (PLS) and a multiple linear regression (MLR) analysis between these two datasets were carried out.
As individuals in these two datasets are from the same population, it is expected that no difference exists between these two datasets.
In general, the overlap between these two datasets was small.
There were 9,217 SNP and 44 bulls in common between these two datasets.
Similar(28)
Differential expression between miRNAs in these two datasets was assessed with NOISeq-sim [ 101] allowing a threshold of 0.9.
This assures that training and test sets have similar number of chains and that similarity between sequences in these two datasets is <30%.
Here we analyse the correlation between water level in the well and vertical ground motions recorded at a nearby surface site, and we examine the relationship between the characteristics of these two datasets and the well-aquifer system parameters.
Given the genetic similarity between populations A and B, these two datasets were pooled.
Here, again, there are differences between these three datasets.
More suggestions(15)
between these two streams
between these two collectives
between these two responsibilities
between these two ages
between these two candidates
between these two points
between these two teams
between these two paths
between these two stances
between these two grids
between these two reversals
between these two constitutions
between these two cultures
between these two media
between these two positions
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CEO of Professional Science Editing for Scientists @ prosciediting.com