Sentence examples for validation of the training from inspiring English sources

Among these methods, the prediction performance of naïve Bayes classifier established here displayed very well and stable, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set I set were 89.1 ± 0.4% and 77.3 ± 1.5%, respectively.

In addition, the results on 5% training data, is likely to be more useful in real-time systems as in real applications the size of the test data keeps on growing at a rate higher than the training data, mainly because of the labor intensive processes involved in the preparation and validation of the training data.

The designing procedure [20] is summarized in four steps: a driven initialization of  MLPs of size is chosen; a set of training algorithm parameters that warrants its stability and convergence [28] is used; an external validation of the training process is applied; and a selection of the best MLP in terms of average SCR improvements is done.

We received good results for each of the single-source classifiers; SVM-based classifiers for RNTech and Asterand had 90.0% and 93.0% predicted accuracies, respectively, according to ten-fold cross validation of the training set (Table 2A).

The best scoring model for the mixed set was using 9 features (Mann-Whitney p-value filter of 0.044) and had a predicted accuracy of 84.1% according to ten-fold cross validation of the training set.

Cross validation of the training sets proved valuable ahead of deciding how to genotype limited case material as it allowed an assessment of both the accuracy and performance of the AIM-SNP ancestry test.

These results were obtained with the out-of-bag (OOB) validation on the training set.

Table S3 in the Supplement summarizes the results of the cross validation on the training set for the nine feature selection setups; 3 (sampling strategies) × 3 (ranking methods).

Primary analysis will consist of a fivefold cross validation on the training set to calculate expected prediction errors.

Full cross-validation of the training set was performed using the leave-one-out method (LOO).

By default, the decision values for calibrating the probability estimates are derived from a fivefold cross-validation of the training data set.