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PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu
ADMA
2010
Springer
248views Data Mining» more  ADMA 2010»
13 years 5 months ago
Classification Inductive Rule Learning with Negated Features
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
Stephanie Chua, Frans Coenen, Grant Malcolm
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
14 years 2 months ago
Representing Tuple and Attribute Uncertainty in Probabilistic Databases
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources — sensor data, experimental data, data from ...
Prithviraj Sen, Amol Deshpande, Lise Getoor
MINENET
2005
ACM
14 years 1 months ago
Topographical proximity for mining network alarm data
Increasingly powerful fault management systems are required to ensure robustness and quality of service in today’s networks. In this context, event correlation is of prime impor...
Ann Devitt, Joseph Duffin, Robert Moloney
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 8 months ago
V-Miner: using enhanced parallel coordinates to mine product design and test data
Analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. This paper proposes a new technique based on parallel coordi...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...