Sentence examples for set prediction from inspiring English sources

The best was a 9 peak SVM (3 k-NN) model which gave 94.4% accuracy on cross-validation and 100% sensitivity, specificity, accuracy, positive predictive value and negative predictive value for test set prediction.

The parameter prediction accuracies from the inverse HC-PLSR metamodel are shown in Figure  6, represented by the correlation coefficients (R 2 -values) between the simulated and the predicted parameters from a test set prediction.

A three-dimensional (3D) quantitative pharmacophore model was developed from a training set of structurally diverse substituted ureas against Raf-1 kinase, which was well validated to be highly predictive by two methods, namely, test set prediction and Cat-Scramble method.

The test set prediction suggests a good correlation between the experimental and predicted activities for both Hypo1_A (correlation coefficient r = 0.86) and Hypo1_B (correlation coefficient r = 0.81) indicates the good prediction ability of both models.

The acceptable parameters of test set prediction, such as Rpred2= 0.768 and rm test)2="0.711 suggested that external predictivity of the model was significant.

Moreover, this score is very similar to that associated with the training set prediction (93%), so the underlying feature of the model is not only predictive but also general.

We performed ENM using the Genetic Algorithm for Rule-set Prediction (GARP) to predict the optimal and potential ecological niche areas of C. gattii in BC.

Distribution maps were generated for historically recorded species using genetic algorithm for rule-set prediction (GARP).

The proposed noncausal image predictor can provide better performance than Sachnev et al.'s noncausal double-set prediction method (where data prediction in two passes brings a distortion problem due to the fact that half of the pixels were predicted with the watermarked pixels).

Comparing with Sachnev et al.'s noncausal double-set prediction method [15], the proposed prediction method can further reduce the prediction errors by predicting data in a single pass (which avoids the distortion problem due to the fact that half of the pixels in the second set predicted with the watermarked pixels in the first set).

The specific ENM chosen for this study was the Genetic Algorithm for Rule-set Prediction (GARP [69]).