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Exact(6)

Firstly, failure prediction models have been implemented through machine learning approaches using evaluated performance metrics and also demonstrates the maximum prediction accuracy for Naive Bayes.

As suggested above, an alternative could be to select PC in the CV procedure based on maximum prediction accuracy.

The process of model building and feature elimination is repeated until the minimum feature subset is obtained which gives a classifier model with the maximum prediction accuracy.

Our best model based on the hybrid approach achieved maximum prediction accuracy of 82.10% with MCC of 0.62 on main dataset.

For lines B1 and W1, the maximum prediction accuracy was in both cases achieved when only the line itself was used both for PCA and in the ridge regression model, and fewer PC were required to reach this maximum accuracy.

Here we decided to set the cutoff high at 50 bits, as depicted in Figure  5, in accordance to the maximum prediction accuracy and to diminish as much as possible the rate of false positives included in the predictions.

Similar(54)

For classifiers trained on feature sets ranging from 1 to 1000 features, we plotted the maximum prediction accuracies of transcript- and marker-based prediction for each SMP; more or fewer features are required for maximum accuracy depending on the SMP.

Figure  1 a,b) demonstrates the adjusted R distributions for these 4,095 mESC TF models and 255 mESC HM+DNase models respectively, with the minimum and maximum prediction accuracies for each n and m connected by the blue and red curves.

Here, we select this hyperparameter by cross-validation, varying η until a maximum in prediction accuracy is reached.

This model provided good prediction accuracy (maximum percentage error 7.45%) of surface roughness.

Time-dependent ROC curves [54] were used to evaluate the prediction accuracy at maximum time point for each data set using the nearest neighbor estimator (survivalROC R package).

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