Purpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms … without shortcomings, suggesting that there is ample room for improvement. This paper briefly introduces clustering techniques … of clustering techniques. Originality/value: To date, there has been no paper comparing the new k-value estimation …

differences between countries in Europe according to how their companies tackled the challenges of IT security. Clustering is …

-means algorithm (Dunn 1973; Bezdek 1981). The algorithm generalizes the K-means methodology of Bonhomme and Manresa (2015) to allow …

The goal of the paper is to present the framework for combining clustering and classification for churn management in … interaction detector (CHAID) decision tree algorithm is used to develop classification models to identify churn determinants at … approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable …

heuristic optimization algorithm. Design/methodology/approach: In the initial stage, a modified form of factor analysis is used …-programming model. A comparison with the k-means++ clustering algorithm, one of the most popular clustering algorithms, was made to … heuristic optimization algorithm for finding optimal routes. …

Expectation Maximization (EM) is a widely employed mixture model-based data clustering algorithm and produces … clustering algorithms. This paper presents an algorithm for the novel hybridization of EM and K-Means techniques for achieving … better clustering performance (NovHbEMKM). This algorithm first performs K-Means and then using these results it performs EM …

clustering was the lowest at 92. 25%. After using evolutionary technique Genetic Algorithm as Feature selection technique, the … is based mostly on three cluster techniques like; K means, Fuzzy c-means and hierarchical clustering. The authors used … evolutionary techniques like genetic algorithms (GA) to extend the performance of the clustering model. The performance of these …

-means clustering in Ganga River Basin Management and real-world feature data for detecting diabetes patients suffering from diabetes …