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137
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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 3 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
133
Voted
CIKM
2006
Springer
15 years 6 months ago
Finding highly correlated pairs efficiently with powerful pruning
We consider the problem of finding highly correlated pairs in a large data set. That is, given a threshold not too small, we wish to report all the pairs of items (or binary attri...
Jian Zhang, Joan Feigenbaum
133
Voted
BMCBI
2010
130views more  BMCBI 2010»
15 years 2 months ago
The behaviour of random forest permutation-based variable importance measures under predictor correlation
Background: Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observ...
Kristin K. Nicodemus, James D. Malley, Carolin Str...
123
Voted
GLOBECOM
2008
IEEE
15 years 2 months ago
Correlation Among Piecewise Unwanted Traffic Time Series
In this paper, we investigate temporal and spatial correlations of time series of unwanted traffic (i.e., darknet or network telescope traffic) in order to estimate statistical beh...
Kensuke Fukuda, Toshio Hirotsu, Osamu Akashi, Tosh...
PAMI
2007
217views more  PAMI 2007»
15 years 2 months ago
Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations
—We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and li...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla