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» Forecasting high-dimensional data
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ICDE
2003
IEEE
146views Database» more  ICDE 2003»
15 years 11 months ago
Similarity Search in Sets and Categorical Data Using the Signature Tree
Data mining applications analyze large collections of set data and high dimensional categorical data. Search on these data types is not restricted to the classic problems of minin...
Nikos Mamoulis, David W. Cheung, Wang Lian
GFKL
2004
Springer
137views Data Mining» more  GFKL 2004»
15 years 3 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
JMLR
2008
117views more  JMLR 2008»
14 years 9 months ago
Closed Sets for Labeled Data
Closed sets have been proven successful in the context of compacted data representation for association rule learning. However, their use is mainly descriptive, dealing only with ...
Gemma C. Garriga, Petra Kralj, Nada Lavrac
PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
15 years 3 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
ESANN
2003
14 years 11 months ago
High-dimensional labeled data analysis with Gabriel graphs
We propose the use of the Gabriel graph for the exploratory analysis of potentially high dimensional labeled data. Gabriel graph is a subgraph of the Delaunay triangulation, which ...
Michaël Aupetit