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JMLR
2010
116views more  JMLR 2010»
13 years 4 months ago
Feature Selection, Association Rules Network and Theory Building
As the size and dimensionality of data sets increase, the task of feature selection has become increasingly important. In this paper we demonstrate how association rules can be us...
Sanjay Chawla
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 10 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICDM
2008
IEEE
127views Data Mining» more  ICDM 2008»
14 years 4 months ago
The Impact of Structural Changes on Predictions of Diffusion in Networks
In a typical realistic scenario, there exist some past data about the structure of the network which are analyzed with respect to some possibly future spreading process, such as b...
Mayank Lahiri, Arun S. Maiya, Rajmonda Sulo, Habib...
SDM
2009
SIAM
291views Data Mining» more  SDM 2009»
14 years 7 months ago
Detection and Characterization of Anomalies in Multivariate Time Series.
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
AUSDM
2007
Springer
100views Data Mining» more  AUSDM 2007»
14 years 4 months ago
Predictive Model of Insolvency Risk for Australian Corporations
This paper describes the development of a predictive model for corporate insolvency risk in Australia. The model building methodology is empirical with out-ofsample future year te...
Rohan A. Baxter, Mark Gawler, Russell Ang