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BMCBI
2011
13 years 3 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
ICDE
2000
IEEE
96views Database» more  ICDE 2000»
14 years 9 months ago
Dynamic Miss-Counting Algorithms: Finding Implication and Similarity Rules with Confidence Pruning
Dynamic Miss-Countingalgorithms are proposed, which find all implication and similarity rules with confidence pruning but without support pruning. To handle data sets with a large...
Shinji Fujiwara, Jeffrey D. Ullman, Rajeev Motwani
KAIS
2006
77views more  KAIS 2006»
13 years 8 months ago
Finding centric local outliers in categorical/numerical spaces
Outlier detection techniques are widely used in many applications such as credit card fraud detection, monitoring criminal activities in electronic commerce, etc. These application...
Jeffrey Xu Yu, Weining Qian, Hongjun Lu, Aoying Zh...
ECEASST
2010
13 years 5 months ago
Self Organized Swarms for cluster preserving Projections of high-dimensional Data
: A new approach for topographic mapping, called Swarm-Organized Projection (SOP) is presented. SOP has been inspired by swarm intelligence methods for clustering and is similar to...
Alfred Ultsch, Lutz Herrmann