Sentence examples for weight of errors from inspiring English sources
We calculated the number of errors (NE, total of 21 decisions), the weight of errors (WE, volume difference of reference and test object), and the direction of errors (DE).
A total of 21 comparisons were performed to assess the number of errors, the weight of errors (ie, the volume difference between test and reference stimuli), and the direction of errors (ie, over- or underestimation of test stimulus).
Attributing such "weight of error" to a small matter of age seems a touch absurd, but both this and indeed his chattiness are the airy indicators of his very solid, serious honesty as a writer.
Saramago concludes this little amendment chattily with, "Anyway, now that I've sorted that out and the weight of error has been lifted from my conscious, I can continue".
where d3 is the minimum weight of error paths in the third error event.
where d2 is the minimum weight of error paths in the second error event, and A is the set of all 64 states.
Different accounts of crowding would predict a differential weighting of errors towards these three types.
In this study, simple averaging has been used to come up with Table 3. Table 3 Weights of different errors Error Correct signal TA signal Error weight Sell for buy Buy Sell 80 Buy for sell Sell Buy 80 Hold for sell Sell Hold 35 Hold for buy Buy Hold 30 Buy for hold Hold Buy 15 Sell for hold Hold Sell 15.
In addition to identifying human error categories, determining and weighting of error-producing conditions (EPCs) is the key aspect of human reliability quantification.
Under this hypothesis, we should expect an attenuation of the weight of fictive errors on a subject's next bet and this attenuation should be accompanied by reduced neural responses to fictive errors but not reward prediction errors (the "experienced" errors in our description above).
The values of γ ( = 0.1) in the above equation and the Cost parameter (which controls the relative weight of training errors on positive examples compared to those on negative examples, and ranges from 3 to 5 depending on the training sample) were determined using a grid-search strategy.
