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» Forecasting high-dimensional data
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CATA
2004
14 years 11 months ago
Decision Tree Induction for Dynamic, High-Dimensional Data Using P-Trees
1 Decision Tree Induction is a powerful classification tool that is much used in practice and works well for static data with dozens of attributes. We adapt the decision tree conce...
Anne Denton, William Perrizo
91
Voted
BMEI
2008
IEEE
14 years 11 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
SIGMOD
2001
ACM
193views Database» more  SIGMOD 2001»
15 years 9 months ago
Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data
The similarity join is an important database primitive which has been successfully applied to speed up applications such as similarity search, data analysis and data mining. The s...
Christian Böhm, Bernhard Braunmüller, Fl...
APWEB
2006
Springer
15 years 1 months ago
Generalized Projected Clustering in High-Dimensional Data Streams
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
Ting Wang
IS
2006
14 years 9 months ago
High dimensional nearest neighbor searching
As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of mult...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...