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Discover LudwigThe phrase "a balanced prediction" is correct and usable in written English.
It can be used when discussing forecasts or estimations that take into account various factors to provide a fair and impartial outlook.
Example: "The analyst provided a balanced prediction of the market trends, considering both optimistic and pessimistic scenarios."
Alternatives: "an impartial forecast" or "a fair estimation".
Exact(1)
In addition, the network setup for optimum AUC area gives a balanced prediction for query sequence, resulting in moderately high (optimum) recall/precision values.
Similar(59)
The RF-original exhibited the most balanced prediction accuracy, with an accuracy of 84.26% for ignitions and 88.35% for nonignitions.
BACC balanced prediction accuracy.
The most balanced prediction model was that in which the three success criteria were included, with age, surgical technique, and infection at surgery being excluded as variables.
Analysis of our results revealed that the new method delivers more balanced predictions than our previous work for mutations in residues with a different secondary structure and solvent accessibility as well as for different magnitudes of stability changes.
In this paper we introduce a balanced Modularity-Maximization Link Prediction (MMLP) model to address this issue.
MCC provides a balanced evaluation of the prediction, especially if the two classes are of different sizes [7, 14].
That means a prediction having multiple binding sites in one sequence and none in the others is much less significant than a prediction having a balanced number of binding sites in each sequence.
To achieve a balanced sensitivity and specificity, only predictions by more than four programmes (using the miRecords analysis) or those identified by Optimised Intersection (which includes both PicTar, TargetScanS) (using TargetCombo analysis) were included in the study.
The results of this work show that we can obtain a balanced accuracy of 0.84 in this prediction task.
On the 80 % training set we used 10-fold cross-validation to select the best prior regularization parameters (L 1 or L 2 and C) using the Matthews correlation coefficient (MCC) as a balanced performance measure [ 72], and the prediction cut-off p c = 0.5.
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