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In this paper we thoroughly investigate various OWA-based linkages in hierarchical clustering on numerous benchmark data sets. The inspected setting generalizes the well-known single, complete, and average linkage schemes, among others. The incorporation of weights into the cluster merge procedure creates an opportunity to make use of experts' knowledge about a particular data domain so as to generate...
Supervised learning is of key interest in data science. Even though there exist many approaches to solving, among others, classification as well as ordinal and standard regression tasks, most of them output models that do not possess useful formal properties, like nondecreasingness in each independent variable, idempotence, symmetry, etc. This makes them difficult to interpret and analyze. For instance,...
The famous Hirsch index has been introduced just ca. ten years ago. Despite that, it is already widely used in many decision-making tasks, like in evaluation of individual scientists, research grant allocation, or even production planning. It is known that the $h$-index is related to the discrete Sugeno integral and the Ky Fan metric introduced in the 1940s. The aim of this paper is to propose a few...
Multi-sensor based classification of professionals' activities plays a key role in ensuring the success of an his/her goals. In this paper we present the winning solution to the AAIA'15 Tagging Firefighter Activities at a Fire Scene data mining competition. The approach is based on a Random Forest classifier trained on an input data set with almost 5000 features describing the underlying time series...
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