Sentence examples for the classifying prediction from inspiring English sources

To observe whether the size of negative dataset influence the classifying prediction performance, another independent negative dataset was prepared (Additional file 10: Text S1).

We used the sequence based version of I-Mutant 3.0 that classifies the prediction into three classes: neutral mutation (−0.5 ≤ DDG ≥ 0.5 kcal/moL), large decrease (<−0.5 kcal/moL), and a large increase (>0.5 kcal/moL).

After selection of predictions according to their sequence and structural features, an effort was made to classify predictions and to validate FindMiRNA combined with the adopted parameters and thresholds as effective instruments for de novo identification.

A threshold was set to enable us to classify predictions into true positives (Tp ), true negatives (Tn ), false negatives (Fn ) and false positives (Fp ).

During testing with the independent test set of 800 TCEs, the operating point (OOP) of the models in classifying their predictions as response or failures to maximise sensitivity and specificity was established.

For the final prediction, classify was called using the 'diaglinear' option, which fits a multivariate normal density to each group with a pooled estimate of covariance with the non-diagonal entries of the covariance matrix set to zero.

Two-dimensional projection is the most desirable, allowing examination of the classification results in terms of recognition ability (percentage of members of the training set correctly classified) and prediction ability (percentage of members of the test set correctly classified using the rules developed during the training).

Instead, they rely on the potentiality of the high-scale experimental assays performed to classify the predictions.

While with this naïve labeling, all three cases are classified atypical, the prediction algorithm is supposed to identify only the second case.

We then classified the predictions into two categories.

Thus, a methodology able not only to identify putative prion domains in large databases of protein sequences, but also to correctly classify the predictions in terms of precision and accuracy would be of high interest.