Evaluation of clustering partitions is a crucial step in data processing. A multitude of measures exists, which - unfortunately - give for one data set various results. In this paper we present a visualization technique to visualize single clusters of high-dimensional data. Our method maps a single cluster to the plane trying to preserve the membership degrees. The resulting scatter plot illustrates separation of the respecting cluster and the need of additional prototypes as well. Since clusters will be visualized individually, additional prototypes can be added locally where they are needed
Information Visualization is commonly recognized as a useful method for understanding sophistication...
We describe a novel approach to the visualization of hierarchical clustering that superimposes the c...
Subspace-based analysis has increasingly become the preferred method for clustering high-dimensional...
In this paper we present a visualization technique to visualize single clusters of high-dimensional ...
Clustering is a powerful analysis technique used to detect structures in data sets. The output of a...
Abstract — In this paper, we re-consider the problem of mapping a high-dimensional data set into a l...
Centroid-based partitioning cluster analysis is a popular method for segmenting data into more homog...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Consider the following dataset, with (only) ten points x=c(.4,.55,.65,.9,.1,.35,.5,.15,.2,.85) y=c(....
Abstract. Subspace clustering (also called projected clustering) addresses the problem that differen...
Subspace clustering addresses an important problem in clustering multi-dimensional data. In sparse m...
Subspace-based analysis has increasingly become the preferred method for clustering high-dimensional...
Visualization can be very powerful in revealing cluster structures. However, directly using visualiz...
Clustering is a major technique in data mining. However the numerical feedback of clustering algorit...
Information Visualization is commonly recognized as a useful method for understanding sophistication...
We describe a novel approach to the visualization of hierarchical clustering that superimposes the c...
Subspace-based analysis has increasingly become the preferred method for clustering high-dimensional...
In this paper we present a visualization technique to visualize single clusters of high-dimensional ...
Clustering is a powerful analysis technique used to detect structures in data sets. The output of a...
Abstract — In this paper, we re-consider the problem of mapping a high-dimensional data set into a l...
Centroid-based partitioning cluster analysis is a popular method for segmenting data into more homog...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mi...
Consider the following dataset, with (only) ten points x=c(.4,.55,.65,.9,.1,.35,.5,.15,.2,.85) y=c(....
Abstract. Subspace clustering (also called projected clustering) addresses the problem that differen...
Subspace clustering addresses an important problem in clustering multi-dimensional data. In sparse m...
Subspace-based analysis has increasingly become the preferred method for clustering high-dimensional...
Visualization can be very powerful in revealing cluster structures. However, directly using visualiz...
Clustering is a major technique in data mining. However the numerical feedback of clustering algorit...
Information Visualization is commonly recognized as a useful method for understanding sophistication...
We describe a novel approach to the visualization of hierarchical clustering that superimposes the c...
Subspace-based analysis has increasingly become the preferred method for clustering high-dimensional...