Sentence examples for using the trained classifier from inspiring English sources

Subsequently, the remaining low-confidence points are classified using the trained classifier.

New examples are then classified using the trained classifier.

New examples, co-cited with the training receptors and ligands, are then classified using the trained classifier.

The semantic category of the left-out exemplar was then predicted using the trained classifier.

Lastly, the classification accuracy was obtained using the trained classifier and the test set.

The probability of classification can be interpreted as a measure of meditation ability by using the trained classifier to predict class membership in novice meditators.

Step 6: Generate the class labels for the remaining points using the trained SVM classifier.

Then, the classification result on the testing subject using the trained SVM classifier was compared with the ground-truth class label, to evaluate the classification performance.

Four-fifth of the data was used to train the classifier and the remaining one-fifth was used to test the trained classifier, where the dataset was randomly partitioned into training and test datasets.

Class probability estimation uses the information of the trained classifier.

The other subset is used to validate the performance of the trained classifier.