Most existing multi-label classification models focus on distance metrics and feature spare strategies to extract specific features of labels. Those models use the cosine similarity to construct the label correlation matrix ...

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem ...

The aim of this study was to evaluate consumers' use and interpretation of ready to drink orange juice and nectar label information and its influence on the purchase decision. One hundred and sixty-seven consumers of ready ...

The aim of this study was to evaluate consumers' use and interpretation of ready to drink orange juice and nectar label information and its influence on the purchase decision. One hundred and sixty-seven consumers of ready ...

A graph G = (V, E) is weighted-k-antimagic if for each w : V -> R, there is an injective function f : E -> {1,...,vertical bar E vertical bar + k} such that the following sums are all distinct: for each vertex u, Sigma(v:uv ...