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IBPRIA
2003
Springer
15 years 9 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
RIDE
1997
IEEE
15 years 8 months ago
Evaluation of Sampling for Data Mining of Association Rules
Discovery of association rules is a prototypical problem in data mining. The current algorithms proposed for data mining of association rules make repeated passes over the databas...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, We...
135
Voted
CVPR
2012
IEEE
13 years 6 months ago
Evaluation of super-voxel methods for early video processing
Supervoxel segmentation has strong potential to be incorporated into early video analysis as superpixel segmentation has in image analysis. However, there are many plausible super...
Chenliang Xu, Jason J. Corso
174
Voted
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
13 years 6 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 4 months ago
Rank based variation operators for genetic algorithms
We show how and why using genetic operators that are applied with probabilities that depend on the fitness rank of a genotype or phenotype offers a robust alternative to the Sim...
Jorge Cervantes, Christopher R. Stephens