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» Benchmarking Data Mining Algorithms
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SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
16 years 3 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh
158
Voted
KAIS
2006
126views more  KAIS 2006»
15 years 6 months ago
Fast and exact out-of-core and distributed k-means clustering
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Ruoming Jin, Anjan Goswami, Gagan Agrawal
MICCAI
2009
Springer
16 years 7 months ago
Constructing a Dictionary of Human Brain Folding Patterns
Abstract. Brain imaging provides a wealth of information that computers can explore at a massive scale. Categorizing the patterns of the human cortex has been a challenging issue f...
Zhong Yi Sun, Matthieu Perrot, Alan Tucholka, Deni...
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
16 years 3 months ago
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
Frederik Janssen, Johannes Fürnkranz
ISNN
2004
Springer
15 years 11 months ago
A Novel Clustering Analysis Based on PCA and SOMs for Gene Expression Patterns
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...
Hong-Qiang Wang, De-Shuang Huang, Xing-Ming Zhao, ...