We describe an interactive way to generate a set of clusters for a given data set. The clustering is done by constructing local histograms, which can then be used to visualize, select, and fine-tune potential cluster candidates. The accompanying algorithm can also generate clusters automatically, allowing for an automatic or semi-automatic clustering process where the user only occasionally interacts with the algorithm. We illustrate the ability to automatically identify and visualize clusters using NCI’s AIDS Antiviral Screen data set. 1
Abstract: Clustering is a well known data mining technique which is used to group together data item...
Most learning algorithms operate in a clearly defined feature space and assume that all relevant str...
This paper introduces an approach for clustering/classification which is based on the use of local, ...
We describe an interactive way to generate a set of clusters for a given data set. The clustering is...
We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a g...
We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a g...
Abstract-We describe an interactive method to generate a set of fuzzy clusters for classes of intere...
Many clustering algorithms have been proposed in recent years. Most methods operate in an iterative ...
Abstract — We describe an interactive method to generate a set of fuzzy clusters for a given data se...
Traditional clustering methods often cannot avoid the problem of selecting neighborhood parameters a...
In this paper, we propose an approach of clustering data in paral-lel coordinates through interactiv...
In this paper, we propose an approach of clustering data in parallel coordinates through interactive...
Fig. 1. Hierarchical clustering results on a synthetic point dataset (the black dots) are shown as a...
Description Visualize cluster results and investigate additional properties of clusters using intera...
In this thesis, a treemap-based interactive clustering algorithm is implemented and evaluated. The t...
Abstract: Clustering is a well known data mining technique which is used to group together data item...
Most learning algorithms operate in a clearly defined feature space and assume that all relevant str...
This paper introduces an approach for clustering/classification which is based on the use of local, ...
We describe an interactive way to generate a set of clusters for a given data set. The clustering is...
We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a g...
We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a g...
Abstract-We describe an interactive method to generate a set of fuzzy clusters for classes of intere...
Many clustering algorithms have been proposed in recent years. Most methods operate in an iterative ...
Abstract — We describe an interactive method to generate a set of fuzzy clusters for a given data se...
Traditional clustering methods often cannot avoid the problem of selecting neighborhood parameters a...
In this paper, we propose an approach of clustering data in paral-lel coordinates through interactiv...
In this paper, we propose an approach of clustering data in parallel coordinates through interactive...
Fig. 1. Hierarchical clustering results on a synthetic point dataset (the black dots) are shown as a...
Description Visualize cluster results and investigate additional properties of clusters using intera...
In this thesis, a treemap-based interactive clustering algorithm is implemented and evaluated. The t...
Abstract: Clustering is a well known data mining technique which is used to group together data item...
Most learning algorithms operate in a clearly defined feature space and assume that all relevant str...
This paper introduces an approach for clustering/classification which is based on the use of local, ...