Decision trees (DTs) epitomize the ideal of interpretability of machine learning (ML) models.
The interpretability of decision trees motivates explainability approaches by so-called …

Non-negative matrix factorization (NMF) has become a popular method for representing
meaningful data by extracting a non-negative basis feature from an observed non-negative …

Land-use classification is essential for urban planning. Urban land-use types can be
differentiated either by their physical characteristics (such as reflectivity and texture) or social …

The purpose of this study is to continue the discussion initiated by Mellinas et al.(2015,
2016) on the effects of the Booking. com rating system and more widely on the use of the …

This paper proposes a process for the classification of new residential electricity customers.
The current state of the art is extended by using a combination of smart metering and survey …

In the current work, a systematic approach is exercised to monitor amended soil reliability for
a housing development program to holistically understand the targeted material mixture and …

In this paper, we propose a generalized wrapper-based feature selection, called GeFeS,
which is based on a parallel new intelligent genetic algorithm (GA). The proposed GeFeS …

Data Mining liefert Grundlagen für die Künstliche Intelligenz, indem es Technologien für die
Analyse großer Datenmengen bereitstellt. Das Buch deckt den Stoff einer einsemestrigen …

Building information is one of the key elements for a range of urban planning and
management practices. In this study, an investigation was performed to classify buildings …

Reliable carbonation depth prediction of concrete structures is crucial for optimizing their
design and maintenance. The challenge of conventional carbonation prediction models is …