Sentence examples for negative classes from inspiring English sources

Subscripts P and N denote positive and negative classes.

For imbalanced data, a classification accuracy can be calculated both for positive and negative classes independently.

Note, each of these tables includes separate scores for the positive and negative classes.

However, for SMOTE pre-processing there is a bias towards the negative classes.

Most of the time, we need only to classify documents into positive and negative classes [65].

In an imbalanced dataset, the positive and negative classes can be quite different in both size and distribution.

In general, once trained, classifiers return probabilities of input samples to be members of the positive or negative classes.

In term of precision and recall, the LNWS method performed on a similar level for both, positive and negative classes.

However, to gather public opinion, authors have considered only strongly positive and strongly negative classes as indicator.

The results of prototype tests have performed a good accuracy in detecting positive and negative classes and their sub-classes.

To train a classifier, a training data set must consist of examples from both positive and negative classes.