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The strategies that made it work are central to Spoon's most successful tracks: reduction, precision, and confusion.
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The results show that in the proposed method, in spite of computational time reduction, better precision is provided as well.
The primary difference in the test set is a reduction in precision for Model 1, resulting in a reduction in f-measure by over 1%.
Here we see that in estimating richer models with leads and lags, there is also a large reduction in precision when geographically proximate controls are included.
A custom data subset for MMTx was created, making it faster and significantly improving the recall to 0.896 with a non-significant reduction in precision.
Little reduction in precision was achieved at the tree level using Model 3, for which mean D was −0.262% with range of −15.2 to 9.74% (Figure 3a) while mean Da was 4.15%, with range of 0.968 to 15.2%.
If there was clear evidence that this reduction in precision was necessary to remove an important source of bias from the estimates, the ADR/DLR estimators might be preferred.
Therefore, a reduction in precision appears to be the consequence of using intraspecific calibrations, but the improvement in accuracy should come as a worthwhile recompense.
Our ultimate goal was to identify the batch adjustment method that best prepares data from multiple batches for analysis or meta-analysis to be integrated, as measured by batch effects reduction, accuracy, precision and overall performance.
The price of this reduced bias was a reduction in precision.
However, since the adjustment is probabilistic, there is likely to be a reduction in precision.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com