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GFKL
2007
Springer
163views Data Mining» more  GFKL 2007»
13 years 11 months ago
Fast Support Vector Machine Classification of Very Large Datasets
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
Janis Fehr, Karina Zapien Arreola, Hans Burkhardt
VLDB
1998
ACM
95views Database» more  VLDB 1998»
13 years 11 months ago
RainForest - A Framework for Fast Decision Tree Construction of Large Datasets
Classification of large datasets is an important data mining problem. Many classification algorithms have been proposed in the literature, but studies have shown that so far no al...
Johannes Gehrke, Raghu Ramakrishnan, Venkatesh Gan...
ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
14 years 12 days ago
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kerneldensity-based clustering with pixel-oriented displays to emphasize c...
Daniel A. Keim, Christian Panse, Mike Sips, Stephe...
KDD
2002
ACM
1075views Data Mining» more  KDD 2002»
14 years 7 months ago
CLOPE: a fast and effective clustering algorithm for transactional data
This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic m...
Yiling Yang, Xudong Guan, Jinyuan You
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 7 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...