Sentence examples for some of the classification from inspiring English sources

Decision tree, fuzzy logic, support vector machine and artificial neural networks are some of the classification algorithms employed for condition monitoring and fault diagnosis.

Some of the classification strategies have been adapted to use a reduced number of features in order to cope with these rare symbols in the same way as with the other common symbols.

If such features were added (e.g., using part-of-speech tags and extraction of terms that contain temporal information), some of the classification errors could probably have been avoided.

Some of the classification errors were a result of the annotators receiving instructions to classify tweets containing any of the emotions fear, anger, or positive as other if the tweets relate to a "historical" state or if the expressed emotion related to someone else than the author of the tweet.

Also, a largest database of training data could allow to use more robustly some of the classification strategies evaluated, like the ones based on the Fisher linear discriminant, which are actually limited by the availability of samples of objects of certain rare classes.

The variability described might also explain some of the classification discrepancies between the two methods.

He read me some of the classifications, which cannot be reprinted here, and we stared at each other, mystified.

Some of the classifications are here reviewed and a choice made at the end.

Figure 1 represents some of the classifications of protein protein complexes discussed below.

The v values on the c branch for some of the classifications proved to be 5 times greater than on the branches a, b, and d.

In case of some of them the classification is tentative: they are pulsating red giants possibly being AGBs or close to the AGB phase.