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GFKL
2004
Springer
117views Data Mining» more  GFKL 2004»
14 years 4 months ago
Cluster Ensembles
Cluster ensembles are collections of individual solutions to a given clustering problem which are useful or necessary to consider in a wide range of applications. The R package˜c...
Kurt Hornik
GFKL
2004
Springer
135views Data Mining» more  GFKL 2004»
14 years 4 months ago
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...
Nils Raabe, Karsten Luebke, Claus Weihs
GFKL
2004
Springer
132views Data Mining» more  GFKL 2004»
14 years 4 months ago
Reservation Price Estimation by Adaptive Conjoint Analysis
Abstract. Though reservation prices are needed for many business decision processes, e.g., pricing new products, it often turns out to be difficult to measure them. Many researcher...
Christoph Breidert, Michael Hahsler, Lars Schmidt-...
GFKL
2004
Springer
82views Data Mining» more  GFKL 2004»
14 years 4 months ago
Quantitative Text Typology: The Impact of Word Length
The present study aims at the quantitative classification of texts and text types. By way of a case study, 398 Slovenian texts from different genres and authors are analyzed as t...
Peter Grzybek, Ernst Stadlober, Emmerich Kelih, Go...
GFKL
2004
Springer
107views Data Mining» more  GFKL 2004»
14 years 4 months ago
Hierarchical Mixture Models for Nested Data Structures
A hierarchical extension of the finite mixture model is presented that can be used for the analysis of nested data structures. The model permits a simultaneous model-based cluster...
Jeroen K. Vermunt, Jay Magidson
GFKL
2004
Springer
97views Data Mining» more  GFKL 2004»
14 years 4 months ago
Exploring Multivariate Data Structures with Local Principal Curves
Jochen Einbeck, Gerhard Tutz, Ludger Evers
GFKL
2004
Springer
137views Data Mining» more  GFKL 2004»
14 years 4 months ago
Density Estimation and Visualization for Data Containing Clusters of Unknown Structure
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
Alfred Ultsch