This work presents a new method for multi-label classification based on Particle Swarm Optimization, called Multi Label K-Nearest Michigan Particle Swarm Optimization ML-KMPSO) and evaluates it experimentally using two ...

Many Machine’s Learning classification problems are described in the literature associanting the classification of data with a belonging class to an finite set of classes, all at a same level. However, many classification ...

The amount of information stored in text databases is steadily increasing. As such, demand for automated techniques to organize this data also continues to grow. In this context, academic and industry research has been ...

Multi-label classification a machine learning task whose objective is to generate models capable of learning relationships between descriptive characteristics of objects and the sets of classes to which such objects belong. ...

Multi-label classification is a machine learning task where instances can be classified into two or more labels simultaneously. In this task, there exist correlations between the instances belonging to same or similar sets ...

Data classification is a task with high applicability in a lot of areas. Most methods for treating classification problems found in the literature dealing with single-label or traditional problems. In recent years has been ...