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» Outlier Detection for High Dimensional Data
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ICCV
2009
IEEE
16 years 2 months ago
Mode-Detection via Median-Shift
Median-shift is a mode seeking algorithm that relies on computing the median of local neighborhoods, instead of the mean. We further combine median-shift with Locality Sensitive...
Lior Shapira, Shai Avidan, Ariel Shamir
ECEASST
2010
14 years 6 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
APBC
2004
121views Bioinformatics» more  APBC 2004»
14 years 10 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...
SDM
2008
SIAM
158views Data Mining» more  SDM 2008»
14 years 11 months ago
Similarity Measures for Categorical Data: A Comparative Evaluation
Measuring similarity or distance between two entities is a key step for several data mining and knowledge discovery tasks. The notion of similarity for continuous data is relative...
Shyam Boriah, Varun Chandola, Vipin Kumar
ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
15 years 3 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan