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ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
14 years 1 months ago
Parallel Algorithms for Distance-Based and Density-Based Outliers
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Elio Lozano, Edgar Acuña
ARTCOM
2009
IEEE
14 years 2 months ago
Image Segmentation - A Survey of Soft Computing Approaches
—Soft Computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found w...
N. Senthilkumaran, R. Rajesh
KES
2006
Springer
13 years 8 months ago
Spiking Neural Network Based Classification of Task-Evoked EEG Signals
This paper presents an improved technique to detect evoked potentials in continuous EEG recordings using a spiking neural network. Human EEG signals recorded during spell checking,...
Piyush Goel, Honghai Liu, David J. Brown, Avijit D...
ESANN
2004
13 years 9 months ago
Neural networks for data mining: constrains and open problems
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
Razvan Andonie, Boris Kovalerchuk
NC
1998
102views Neural Networks» more  NC 1998»
13 years 9 months ago
Outliers and Bayesian Inference
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Peter Sykacek