Sentence examples for label classification from inspiring English sources

This section discusses past efforts on emotion detection in music, mainly in terms of emotion model, extracted features, and the kind of modeling of the learning problem: (a) single label classification, (b) regression, and (c) multi-label classification.

Also, our approach is applicable to single-label classification, multi-label classification, as well as regression problems.

Binary relevance corresponds to the baseline of multi-label classification.

Single-label classification and regression cannot model this multiplicity.

This way, CLR manages to perform multi-label classification.

They transform the multi-label classification task into one or more single-label classification, regression, or ranking tasks.

An application to multi-label classification (in which each learning instance can belong to several classes simultaneously) is demonstrated.

Extensive multi-label classification experiments were conducted on data sets of different scale.

LAIM is inspired in the discretization heuristic of CAIM for single-label classification.

Section 6 presents experimental results comparing the seven multi-label classification algorithms.

In the multi-label classification experiment, each node is assigned to one or more class labels.