The intelligent LINEX k-means clustering is a generalization of the k-means clustering so that the number of clusters and their related centroid can be determined while the LINEX loss function is considered as the dissimilarity measure. Therefore, the selection of the centers in each cluster is not randomly. Choosing the LINEX dissimilarity measure helps the researcher to overestimate or undere...

identifying clusters or clustering is an important aspect of data analysis. it is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. it is a main task of exploratory data mining, and a common technique for statistical data analysis this paper proposed an improved version of k-means algorithm, namely persistent k...

k-means++ is a seeding technique for the k-means method with an expected approximation ratio of O(log k), where k denotes the number of clusters. Examples are known on which the expected approximation ratio of k-means++ is Ω(log k), showing that the upper bound is asymptotically tight. However, it remained open whether k-means++ yields an O(1)-approximation with probability 1/poly(k) or even wi...

a well-known algorithm of clustering is k-means by which the data are divided into k classes based upon a distance criterion. in the present research, by using k-means method for classifying data derived from exploration boreholes in the parkam deposit, the optimum k has been calculated and then the data have been clustered and the relative geochemical behavioral characteristics analyzed. the c...

.......................................................................................................2 Background .................................................................................................5 Stars and Spectroscopy with the Spitzer Space Telescope .................................5 Clustering Methodologies .....................................................................

Cardiac fibre architecture plays a key role in heart function. Recently, the estimation of fibre structure has been simplified with diffusion tensor MRI (DT-MRI). In order to assess the heart architecture and its underlying function, with the goal of dealing with pathological tissues and easing inter-patient comparisons, we propose a methodology for finding cardiac myofibrille trace corresponde...

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...

В настоящее время происходит активное накопление данных большого объёма в различных информационных средах, таких как социальные, корпоративные, научные и другие. Интенсивное использование больших данных в различных областях стимулирует повышенный интерес исследователей к развитию методов и средств обработки и анализа массивных данных огромных объёмов и значительного многообразия. Одним из персп...

Software projects are usually analyzed by experts based on their previous experience, their intuition and data they gather about the project. In this work, we show an approach for a purely data-driven retrospective project analysis. We plan to build on this work to make predictions about the evolution of software projects.