Sentence examples for confidence instances from inspiring English sources

To prevent this behavior and to direct the learner to low confidence instances but also to unexplored regions in instance space, the d-Confidence value of a point is high in the neighborhood of known instances decreasing with the distance to those (Fig. 3b).

We found a marked double dissociation between objective response and subjective confidence: instances in which subjects systematically responded correctly at very low confidence and others in which subjects responded systematically incorrectly with very high confidence in their response.

By restricting prediction to high confidence instances only we can further improve predictive accuracy.

Specifically, we consider cautious classification in which we decline to make predictions if the confidence is sufficiently low but make predictions of a link or nonlink in high confidence instances.

Apart from indicating the reliability of a prediction, this confidence measure can be used to rank predictions and to further enhance predictive accuracy via cautious classification, i.e. by restricting predictions to high confidence instances, we achieve greater accuracy, but at the expense of only making predictions on a fraction of variants.

We showed that there are significant gains from using cautious classification, where prediction is confined to a high confidence instance.

Hits or targets of a transcription factor were identified as those genes with a high confidence instance of the associated binding site in their 2000 bp upstream region (for details see Figure 2 and Methods).

α t = ln ⁡ (− ε t 1 − ε t ) W i t + 1 = W i t e − a t h y i t (x → i ) P i t + 1 = W i t + 1 ∑ i = 1 N W i t + 1 t = t + 1 ; End The confidence instance x → belonging?

The proposed method was composed of cautious classification and data cleaning, where cautious classification was used to increase the accuracy by restricting predictions to high-confidence instances, whereas data cleaning was used to mitigate the influence of mislabeled training instances.

By associating a probability measure with classifier predictions, we enable cautious classification, which can increase accuracy by restricting predictions to high-confidence instances, and data cleaning that can mitigate the influence of mislabeled training instances.

When discussing confidence, for instance, I ask first what this confidence thing is that people want more of.