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The precision, accuracy, F-score thresholds produce similar performance profiles, while the recall threshold produce a profile with elevated recall and lowered precision.
In comparison to the other metrics, the recall-based thresholds produce a distinctly separate profile with elevated recall and lowered precision, with many of the model performances populating an area of high recall and precision.
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Excluding other hypotheses one by one (Models 3, 4, 5 and 6) lowers precision considerably.
Generally, we obtain increased relative saving for lower precision.
This kind of method takes much time with lower precision.
A larger value of SD corresponds to a lower precision in spike timing.
A subword is a lower precision of data contained within a word.
For all these four lower precision multiplication, RCMB algorithm is applied.
This is can be justified by the lower precision value achieved by the fuzzy algorithm.
By exploiting SWP in signed multipliers, multiple lower precision multiplications can be performed.
Totally, four muxes are added in the second lower precision region.
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