Sentence examples for much lower error from inspiring English sources

Exact(10)

The proposed scheme provides a much lower error probability in comparison with existing cooperative protocols.

So with more activity so far, and it's a very short period, we have a much lower error rate.

Data with non-overlapping intervals (red + symbols) show higher scattering, the ones calculated with overlapping intervals (green ×) show a much lower error.

It was observed that the fixed-gain AF-FD relaying has much lower error floor with respect to the variable-gain AF-FD relaying.

Many observers of Echo's success thus far, myself included, have suggested that part of the reason Alexa's voice interaction works so well is because it's really the only option – people don't consistently use Siri or Google Now because they don't have to; manipulating the touch screen has a much lower error rate in terms of accomplishing what you intended to do.

These settings will produce very short contigs, but will also give a much lower error rate than a regular Velvet run.

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Similar(50)

Although the Li et al. model attempts to control for factors that might increase error (such as scanner bias), the errors between the two approaches are comparable (Fig. 1B) with GLAM having slightly higher errors for target concentrations less than 4 pM, but much lower errors for target concentrations >4 pM.

Bininda-Emonds and Sanderson found that wMRP-MP was more accurate than CA-MP, whereas, across all model conditions, our study found that CA-MP was more accurate than wMRP-MP, having much lower FN error rates and comparable FP error rates.

Therefore, much lower SNP error rates are expected (30% of the consensus base substitution error rate), about 0.01% for SOLiD, 0.04% for Solexa and 0.08% for Roche 454 (Table 3).

In addition, the SVM model has a root-mean-square error of class predicted probability (RMSECPP) of 0.07, showing a much lower prediction error compare to PLS-DA model, which had an RMSEP value of 0.21.

Random Forest constructed a better predictive model than multinomial logistic regression, showing comparable predictive uncertainty but much lower validation error.

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