. Beneficiaries express satisfaction with the Project but have limited understanding of its rationale. The clustering method, which …

various non-parametric clustering models to detect outliers, and assesses their effectiveness using different quality criDer … Clustering-Modelle, um auffällige Werte aufzudecken und nach verschiedenen Gütekriterien deren Wirkung zu bewerten. Als geeignet … various non-parametric clustering models to detect outliers, and assesses their effectiveness using different quality criteria …

their mesoregions. We applied a four-stage methodology, compared the results of two agglomerative clustering methods, and …

-step hybrid model based on machine learning methods for clustering and classification. First, we assign price states to historical … prices using K-means clustering. These price states are also assigned to the corresponding data of external factors. Second …

approach based on mathematical programming and clustering. Finally, we evaluate the performance of the existing networks in …

environment. In this paper, various selected renowned clustering approaches are evaluated with regard to their pattern recognition … number of clusters, the main clustering application, and the performance evaluation. Hence, quantified Term Document Matrices … of clustering techniques by considering the information regarding the optimal number of clusters and by measuring the …

paper, we propose a new methodological framework based on graph clustering and stochastic optimization to support …

networks, such as connectivity, clustering, and the degree of the players, help to predict informed behavior in the lab. People …