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MLDM
2007
Springer
13 years 11 months ago
Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems
In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM...
Trevor Parsons, John Murphy, Patrick O'Sullivan
KDD
1995
ACM
95views Data Mining» more  KDD 1995»
13 years 9 months ago
Limits on Learning Machine Accuracy Imposed by Data Quality
Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the ...
Corinna Cortes, Lawrence D. Jackel, Wan-Ping Chian...
PKDD
2004
Springer
324views Data Mining» more  PKDD 2004»
13 years 10 months ago
Orange: From Experimental Machine Learning to Interactive Data Mining
Abstract. Orange (www.ailab.si/orange) is a suite for machine learning and data mining. It can be used though scripting in Python or with visual programming in Orange Canvas using ...
Janez Demsar, Blaz Zupan, Gregor Leban, Tomaz Curk
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 5 months ago
Relational data pre-processing techniques for improved securities fraud detection
Commercial datasets are often large, relational, and dynamic. They contain many records of people, places, things, events and their interactions over time. Such datasets are rarel...
Andrew Fast, Lisa Friedland, Marc Maier, Brian Tay...
HPDC
2008
IEEE
13 years 12 months ago
Issues in applying data mining to grid job failure detection and diagnosis
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
Lakshmikant Shrinivas, Jeffrey F. Naughton