GeoZ: a Region-Based Visualization of Clustering Algorithms

Novel Graph Based Clustering and Visualization Algorithms for Data Mining

A Comparative Study of Some Clustering Algorithms on Shape Data

Recently, some statistical studies have been done using the shape data. One of these studies is clustering shape data, which is the main topic of this paper. We are going to study some clustering algorithms on shape data and then introduce the best algorithm based on accuracy, speed, and scalability criteria. In addition, we propose a method for representing the shape data that facilitates and ...

Towards a GeoZ Toolkit

The use of Geometric Logic as the foundation of a speciication language called GeoZ is proposed elsewhere 4]. In this note we explore GeoZ from the perspective of practitioners, who are familiar with the existing Z notation, by explaining the issues that arise and the essential role of schema entailment in the GeoZ reformulation of Z's mathematical toolkit.

A Clustering Algorithm Based on Information Visualization

This p aper st udies a clustering algorithm b ased on i nformation visulization. In th is alg orithm, through a nonlinear ma pping (NLP), s ome hig h-dimensional and complicated f eature data i s transformed into low-dimensi onal feature d ata, such as o ne, two and three dim ensionality. I ts mai n aim is that the geometry i mage in high-dimensional s pace is ma pped in to one, two a nd three ...

Geometric visualization of clusters obtained from fuzzy clustering algorithms

Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, the memberships that result from fuzzy-clustering algorithms are difficult to be analyzed and visualized. The memberships, usually converted to 0-1 values, are visualized using parallel coordinates or different color sha...