Sentence examples for raw prediction from inspiring English sources

Raw prediction outputs are provided in Additional file 3: Dataset 2c-h.

At the same time, raw prediction scores by MutaCYP appear to be orthogonal to those by other evaluated methods.

Finally, we measured the correlation in predictions between the four methods by looking at the raw prediction scores (Tables  4 and 5).

Since MutaCYP appears orthogonal to other evaluated methods by showing only moderate correlation in raw prediction scores, there is possibility in improvement of overall prediction by combining two or more methods in a consensus-based classifier.

Meanwhile, as this simple raw prediction method was based only on individual level copy number state data, false positive noises in each individual might also increase the total number of predicted CNVs when sample size increased.

The main reasons for the improvements are the application of a comprehensive set of information sources including complementary disorder predictions, sequence profiles and other relevant sequence-based predictors of structural and functional protein characteristics, novel two-layer architecture and the usage of custom features that aggregate raw prediction inputs.

So here's one man's raw, naked prediction: "I'm not being totally facetious when I say that business travel will be just as awful as it is today," said Mr. Boyd, the president of Boyd Group International, an industry forecasting company.

Because the number of predicted ncRNAs was surprisingly high, we compared the automated raw predictions (before manual curation) with the set of 1102 small RNA candidates proposed in the previous RNA-Seq study of Schlüter et al. In that study, sRNAs candidates were arbitrarily classified as trans-encoded, cis-encoded sense, cis-encoded antisense and mRNA leaders.

The autocorrelations of the scores tend to be slightly bigger in absolute value, reflecting the fact that they are not weakened by outliers in the same way as the raw predictions errors.

In place of the TAS, the raw predictions were used and the values were not combined to a single score, but used directly as inputs to the linear regression.

Our method utilizes a custom-designed set of features that are based on raw predictions and aggregated raw values and recognizes various types of disorder.