Sentence examples for assess the performance of the classifier from inspiring English sources

Furthermore, the receiver operating curve (ROC) was calculated to assess the performance of the classifier over its entire operating range.

Note that in our context the minimization of the validation error is only needed to obtain reliable classifications for the given data and not to assess the performance of the classifier on new data.

The training set is the one that will train the classifier parameter, while the test set is used to assess the performance of the classifier in terms of classification accuracy, F-score value, the area under the receiver operator characteristic curve, precision and recall rates.

With every successive iteration, the testing data was used to assess the performance of the classifier with a lower number of features compared to the previous iteration.

Four independent validation sets were used to assess the performance of the classifier.

In such cases, given the class conditional matrix, potential users may conduct their own studies and assess the performance of the classifier using the method we have described.

To assess the performance of the classifiers on the independent validation dataset, we constructed an ROC curve (Figure 1, Step 8).

We assess the performance of the classifiers against the patients' clinical outcomes.

For assessing the performance of the classifier, the predictions were compared to the gold standard from the experimental screens.

The use of positive (interacting pairs of proteins) and negative (non-interacting pairs of proteins) examples is required for training and assessing the performance of the classifier.

Hence, in the case of unbalanced datasets, the correlation coefficient (CC) or the area under the Receiver Operating Characteristic (ROC) curve (AUC) provide more useful measures than accuracy in assessing the performance of the classifiers [26].