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Each collimated laser beam illuminates the object under interest with θ R, θ G, and θ B angles, respectively for the red, green, and blue lines leading to the three sensitivities.
Violation of rules involving combinations of these three sensitivities, has drastic effect on the resulting confidence intervals.
The FFS process builds this "importance metric" by iterating the analysis of the weight vectors of randomly assigned training folds 10,000 times employing three sensitivity settings, where these three sensitivities score the top 20, 30, and 150 most influential performers for each of their respective 10,000 runs, based on each feature's weight in the weight vector of L-PLS.
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The object is illuminated from three directions, which produces three sensitivity vectors and, subsequently, a three-sensitivity measurement.
Estimated odds ratios from all three sensitivity analyses were consistent with those derived from the actual drug testing data (Appendix).
However, the potential impact of missing PRO data on the results was examined using three sensitivity analyses.
The marginal effect of utility components is captured by three sensitivity coefficients, namely reward, price, and distance sensitivity.
To explore the modelling further we undertook three sensitivity analyses for each comparison.
We performed three sensitivity analyses.
Three sensitivity analyses tests were performed.
Three sensitivity analyses yielded negative results.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com