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In our approach, the value of the objective function J indicates how well the data are separated in the transformed feature space.
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The data were separated in Zone 1 (below the tropic of cancer, i.e., ≤23.5°N) and Zone 2 (above the tropic of cancer, i.e., ≥23.5°N).
For Siemens Biograph 64, list mode data were separated in prompt and random sinograms, and images were reconstructed using attenuation weighted ordered subset expectation maximization without PSF (Iterative3D) and with PSF (TrueX).
For Supervised discretisation the data is separated in intervals as homogeneous as possible in relation to class content.
Hence, in order to identify the specific connections in the networks mediating information flow during stimulation by other ligands, the data was separated in Toll and non-Toll sets.
Moreover, different types of data are separated by placing them in different disks-circles interconnected between each other.
In each experimental data, the genes are separated in two classes corresponding to genes with a large or small phenotypic impact.
Of necessity we have therefore correlated institution level data from snapshots which are separated in time.
2D noisy image patches are separated in 3D data groups.
(3) VM state data is separated from disk image data in a snapshot.
Data reduction is separated in different steps and the intermediate results may be checked if necessary.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com