22 search results - page 3 / 5 » DBOD-DS: Distance Based Outlier Detection for Data Streams |
KDD
2008
ACM
14 years 6 months ago
2008
ACM
Detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. All...
CSDA
2011
12 years 9 months ago
2011
Multivariate outlier identification requires the choice of reliable cut-off points for the robust distances that measure the discrepancy from the fit provided by high-breakdown...
AMW
2010
13 years 7 months ago
2010
Discovering the patterns in evolving data streams is a very important and challenging task. In many applications, it is useful to detect the dierent patterns evolving over time and...
EUSFLAT
2009
13 years 3 months ago
2009
Fuzzy C-Means (FCM) and hard clustering are the most common tools for data partitioning. However, the presence of noisy observations in the data may cause generation of completely ...
KDD
2007
ACM
14 years 6 months ago
2007
ACM
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...