Arbeitspapier
KMC/EDAM : A new approach for the visualization of K-Means Clustering results
In this work we introduce a method for classification and visualization. In contrast to simultaneous methods like e.g. Kohonen SOM this new approach, called KMC/EDAM, runs through two stages. In the first stage the data is clustered by classical methods like K-means clustering. In the second stage the centroids of the obtained clusters are visualized in a fixed target space which is directly comparable to that of SOM.
- Language
-
Englisch
- Bibliographic citation
-
Series: Technical Report ; No. 2004,65
- Event
-
Geistige Schöpfung
- (who)
-
Weihs, Claus
Luebke, Karsten
Raabe, Nils
- Event
-
Veröffentlichung
- (who)
-
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
-
Dortmund
- (when)
-
2004
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Weihs, Claus
- Luebke, Karsten
- Raabe, Nils
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2004
Other Objects (12)
Classification and Clustering in Business Cycle Analysis
Clustering techniques for the detection of business cycles
Identification of Musical Instruments by means of the Hough-Transformation
Improving supervised music classification by means of multi-objective evolutionary feature selection
KMC/EDAM: A new approach for the visualization of K-Means Clustering results
Ensuring an efficient turning process by means of desirability index optimization for correlated quality criteria
A note on the behaviour of the process capability index C_pmk with asymmetric specification limits
Pareto-Optimality and Desirability Indices
Desirability to characterize process capability
Uncertainty of the optimum influence factor levels in multicriteria optimization using the concept of desirability
Business cycle prediction using support vector methods
Stability of multivariate representation of business cycles over time
Classification and Clustering in Business Cycle Analysis
Clustering techniques for the detection of business cycles
Identification of Musical Instruments by means of the Hough-Transformation
Improving supervised music classification by means of multi-objective evolutionary feature selection
KMC/EDAM: A new approach for the visualization of K-Means Clustering results
Ensuring an efficient turning process by means of desirability index optimization for correlated quality criteria
A note on the behaviour of the process capability index C_pmk with asymmetric specification limits
Pareto-Optimality and Desirability Indices
Desirability to characterize process capability
Uncertainty of the optimum influence factor levels in multicriteria optimization using the concept of desirability
Business cycle prediction using support vector methods
Stability of multivariate representation of business cycles over time
Classification and Clustering in Business Cycle Analysis
Clustering techniques for the detection of business cycles
Identification of Musical Instruments by means of the Hough-Transformation
Improving supervised music classification by means of multi-objective evolutionary feature selection
KMC/EDAM: A new approach for the visualization of K-Means Clustering results
Ensuring an efficient turning process by means of desirability index optimization for correlated quality criteria
A note on the behaviour of the process capability index C_pmk with asymmetric specification limits
Pareto-Optimality and Desirability Indices
Desirability to characterize process capability
Uncertainty of the optimum influence factor levels in multicriteria optimization using the concept of desirability
Business cycle prediction using support vector methods