Sentence examples for prediction ranging from from inspiring English sources

Figure 4 shows our accuracy in EU and SA as a function of confidence of the algorithm on its prediction, ranging from the top 25% to the entire dataset (100%) with a training set of 10k users.

The performance of the ANOLEA/ROI predictor is better than the All predictor, with associated p-values for successful prediction ranging from 3.0⋅10−2 to 4.2⋅10−32.

Most of the errors in P prediction ranged from − 25.0% to 25.0%.

The multiclass accuracy of the combined prediction ranges from 33 to 56% depending on cancer classes of testing sets, as compared to 11% for a random prediction among 9 traits.

The theoretical pI prediction ranged from 4.21 to 6.12, based on differences found in the amino acid compositions of the putative laccases.

Accuracies of prediction ranged from 0.53 to 0.72 for ASI and 0.43 to 0.58 for PPT, respectively.

The sensitivity of SF height measurement for SGA (BW < 10th percentile) prediction ranged from 0.27 to 0.76 and specificity ranged from 0.79 to 0.92.

Root mean squared error of prediction ranged from 32 to over 100%% of the mean and varied considerably by which states were included or predicted.

The simulated per-day shift above the baseline prediction ranged from 1 to 5 standard deviations in our simulations, so testing one day at a time could fail to detect those outbreak having small per-day shifts.

In silico prediction using PITA algorithm (Kertesz et al, 2007) revealed here an allele dependent variable binding of miR‐181 species in case of G versus A. For the G allele, the ∆∆G prediction ranges from −3.84 to −9.90; for the A allele, it is 0 (AA is the proautistic risk genotype in our model) (Fig  5).

A poll of polls by broadcaster RTE found that all surveys resulted in a Yes victory, with predictions ranging from 53 per cent to 69 per cent in favour.