Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

In the field of data mining, clustering has shown to be an important technique. Numerous
clustering methods have been devised and put into practice, and most of them locate high …

Internet of Things (IoT) technologies can greatly benefit from machine-learning techniques
and artificial neural networks for data mining and vice versa. In the agricultural field, this …

Mental fatigue is a psychophysiological state that has an intense adverse effect on the
quality of life, undermining both the mental and the physical health. As a consequence …

The purpose of the theoretical considerations and research conducted was to indicate the
instruments with which the quality of a dataset can be verified for the segmentation of …

Diabetes is a complex disease that can lead to serious health complications if left
unmanaged. Early detection and treatment of diabetes is crucial, and data analysis and …

Abstract Human Activity Recognition (HAR) is an important research area that has profound
applications in healthcare, security and surveillance. Starting from traditional machine …

Internal cluster validity measures (such as the Calinski–Harabasz, Dunn, or Davies–Bouldin
indices) are frequently used for selecting the appropriate number of partitions a dataset …

Clustering is a set of essential mathematical techniques in artificial intelligence and machine
learning for analyzing massive amounts of data generated by applications. Clustering uses …

Distance calculation is straightforward when working with pure categorical or pure numerical
data sets. Defining a unified distance to improve the clustering performance for a mixed data …