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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 5 months ago
Detecting outliers using transduction and statistical testing
Outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. Although there has been a significant amount of work in outlier detection, ...
Daniel Barbará, Carlotta Domeniconi, James ...
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
13 years 8 months ago
Use of statistical outlier detection method in adaptive evolutionary algorithms
In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of...
James M. Whitacre, Q. Tuan Pham, Ruhul A. Sarker
ICDM
2002
IEEE
188views Data Mining» more  ICDM 2002»
13 years 9 months ago
A Comparative Study of RNN for Outlier Detection in Data Mining
We have proposed replicator neural networks (RNNs) as an outlier detecting algorithm [15]. Here we compare RNN for outlier detection with three other methods using both publicly a...
Graham J. Williams, Rohan A. Baxter, Hongxing He, ...
ICDM
2008
IEEE
176views Data Mining» more  ICDM 2008»
13 years 11 months ago
Inlier-Based Outlier Detection via Direct Density Ratio Estimation
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inlier...
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...
KAIS
2011
97views more  KAIS 2011»
12 years 11 months ago
Statistical outlier detection using direct density ratio estimation
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...