Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...

A multi-class classification problem is one where the goal is to predict a discrete variable that has three or more possible values. For example, you might want to predict a person's political leaning ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

The chain of the first 3 blocks can be organized in a parallel multi-channel structure that is followed by one or several aggregation blocks. The final decision about the class is made based on the ...