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We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper.
Using multiple correspondence analysis (MCA) [23], these feature profiles were graphically displayed in a plane representing the two main dimensions of variability.
Generally, microarray data is information-rich, with multiple dimensions of variability.
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A formal scaling procedure also was applied to these data to confirm that, indeed, the largest dimension of variability among the students was service productivity.
Using the classifications from the two dimensions of shot variability, we define a simple mapping function to determine the overall shot class, viz: (27).
Here we explored other dimensions of this variability.
SVD is a feature generation technique that facilitates the exploration of multiple dimensions of data variability.
To incorporate additional dimensions of spatial variability, we develop a diffusion model in a second spatial domain Ω.
The spatial and temporal dimensions of this variability can be expressed as schematic plots that are often referred to as "Stommel" diagrams.
The first dimension represents 59.4% of variability and the second dimension represents only 34.6% of variability.
Modeling the PK dimension of human variability.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com