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FLAIRS
2008
15 years 6 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
139
Voted
KDD
2001
ACM
181views Data Mining» more  KDD 2001»
16 years 4 months ago
Identifying non-actionable association rules
Building predictive models and finding useful rules are two important tasks of data mining. While building predictive models has been well studied, finding useful rules for action...
Bing Liu, Wynne Hsu, Yiming Ma
PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
15 years 9 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
ICMLA
2004
15 years 5 months ago
Reducing complexity of rule based models via meta mining
Complexity, or in other words compactness, of models generated by rule learners is one of often neglected issues, although it has a profound effect on the success of any project t...
Lukasz A. Kurgan
KDD
2005
ACM
170views Data Mining» more  KDD 2005»
16 years 4 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua