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» Unsupervised Outlier Detection in Time Series Data
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CSDA
2006
103views more  CSDA 2006»
13 years 8 months ago
LASS: a tool for the local analysis of self-similarity
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic selfsimilarity) in stationary time series. Many methods have been developed for the estimat...
Stilian Stoev, Murad S. Taqqu, Cheolwoo Park, Geor...
ASC
2008
13 years 8 months ago
Info-fuzzy algorithms for mining dynamic data streams
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
DATAMINE
2006
127views more  DATAMINE 2006»
13 years 8 months ago
Computing LTS Regression for Large Data Sets
Least trimmed squares (LTS) regression is based on the subset of h cases (out of n) whose least squares t possesses the smallest sum of squared residuals. The coverage h may be se...
Peter Rousseeuw, Katrien van Driessen
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
14 years 8 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
ICARIS
2003
Springer
14 years 1 months ago
An Investigation of the Negative Selection Algorithm for Fault Detection in Refrigeration Systems
Supermarkets lose millions of pounds every year through lost trading and stock wastage caused by the failure of refrigerated cabinets. Therefore, a huge commercial market exists fo...
Dan W. Taylor, David Corne