Sentence examples for binary predictions from inspiring English sources

The network aggregation procedure described in this article provides a statistically sound way of merging predicted networks or any other binary predictions given a sufficiently large sample space.

We designed the proposed predictor (which includes selection of features that are used to encode the inputs, parameterization of the Support Vector Machine (SVM -based claSVM -basednd seleclassifierse threshold for the predicted disorder probandlitieselectionin binary predictiofs) using 5-fold cross validathen on thresholdataset.

If binary predictions are required, class-specific cut-off thresholds can be applied.

Step 3 shows the optional application of the binary decision thresholds, as the software allows either output binary predictions or the raw probabilistic output of the predictions.

Such thresholds allow the models to more precisely generate binary predictions based on a calculated probability of activity, i.e. activity if Pa ≥ threshold.

Indeed, 154 of the targets show significantly high (≥0.5) enrichment values, revealing that the binary predictions produce considerably superior predictions in many cases.

This approach is also successful at predicting which PDZ domain peptide pairs are likely to interact (binary prediction).

The trained classifier then outputs a binary prediction for any new group instance defined in the same feature space.

The tools give a binary prediction, therefore, they are represented as a point on the ROC plot.

Furthermore, when comparing the names of cities as a binary prediction, we find an accuracy of 32%, while the Null Model has an accuracy near zero.

When achieving the given maximum iteration times T, the intersection of the binary prediction value of (f_{d_1}^T) and (f_{d_2}^T) is used for decision.