Sentence examples for a maximal accuracy of from inspiring English sources

It turns out that the stationary point equations are fulfilled with an average accuracy over all states and stationary points of 0.002 and a maximal accuracy of 0.006, which both is (<10^{-2}).

However, we obtained anAUC of0.853 and a maximal accuracy of 0.789, suggesting a slightly reduced prediction power when discarding RNA secondary structure information (Additional file 2).

On classification of group II alternatively spliced exons against a constitutive background, we achieved a maximal accuracy of ∼66% and AUC of 0.71 in IMR90.

In H, we achieved a similarly high level of accuracy of performance with a maximal accuracy of 78% and AUC of 0.87.

At best, we achieved a maximal accuracy of 80% and AUC of 0.88 for classifying distal group II alternative exon intron boundaries against the constitutive background in IMR90.

In H, we observed the same trend (data not shown) and obtained a maximal accuracy of 76.5% and AUC of 0.84 for classification of group I exon intron junctions against distal constitutive ones.

Based on the predicted optimal parameters, we obtained an AUC of 0.875) and an maximal accuracy of 0.803), which are both higher than the MEME-based prediction, of which the AUC is 0.86 and maximal accuracy is 0.78 [ 5].

We observed that we could obtain a considerably higher accuracy of classification of group II alternatively spliced exons in H if we considered a negative set that was composed of constitutive exons in both H and IMR90, rather than just H with an improvement in maximal accuracy of approximately 4%.

We obtained the best possible accuracy of classification with an AUC of 0.84 and maximal accuracy of 77.1% by using a filtering distance of 10 kb for determining the set of distal constitutive exon intron boundaries in IMR90.

On a more positive side, the maximal accuracy of simple CV reflected closely the nested CV accuracy under each of the settings S1 S4, suggesting that the information content in the quantitative Kd data set make the simple and nested CV strategies comparable in terms of performance estimation.

The maximal accuracy of 84% could be found at a cut-off of 5.5.