Thanks to the Automatic Identification System (AIS), ships and other maritime equipment are able communicate with each other, for example, by sending information about their position. This solution allows early collision detection when two or more on a course. In newer version of AIS, satellite infrastructure is used extend communication range. Unfortunately, AIS deals so-called packet effect: ...

This paper proposes an ensemble method for multilabel classification. The RAndom k-labELsets (RAKEL) algorithm constructs each member of the ensemble by considering a small random subset of labels and learning a single-label classifier for the prediction of each element in the powerset of this subset. In this way, the proposed algorithm aims to take into account label correlations using single-...

Background: According to Cobanoglu et al and Murphy, it is now widely

Multi-label classification deals with the problem where each instance is associated with multiple class labels. Because evaluation in multi-label classification is more complicated than singlelabel setting, a number of performance measures have been proposed. It is noticed that an algorithm usually performs differently on different measures. Therefore, it is important to understand which algori...

The problem of high dimensionality in multi-label domain is an emerging research area to explore. A strategy is proposed to combine both multiple regression and hybrid k-Nearest Neighbor algorithm in an efficient way for high-dimensional multi-label classification. The hybrid kNN performs the dimensionality reduction in the feature space of multi-labeled data in order to reduce the search space...

To recognize individual activities in multi-resident environments with pervasive sensors, some researchers have pointed out that finding data associations can contribute to activity recognition and previous methods either need or infer data association when recognizing new multi-resident activities based on new observations from sensors. However, it is often difficult to find out data associati...

Motivated by an increasing number of new applications, the research community is devoting an increasing amount of attention to the task of multi-label classification (MLC). Many different approaches to solving multi-label classification problems have been recently developed. Recent empirical studies have comprehensively evaluated many of these approaches on many datasets using different evaluat...