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» Mining Several Data Bases with an Ensemble of Classifiers
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ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 5 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
KDD
2006
ACM
191views Data Mining» more  KDD 2006»
14 years 8 months ago
Beyond classification and ranking: constrained optimization of the ROI
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...
Lian Yan, Patrick Baldasare
AUSDM
2008
Springer
227views Data Mining» more  AUSDM 2008»
13 years 9 months ago
Exploratory Mining over Organisational Communications Data
Exploratory data mining is fundamental to fostering an appreciation of complex datasets. For large and continuously growing datasets, such as obtained by regular sampling of an or...
Alan Allwright, John F. Roddick
IRI
2005
IEEE
14 years 1 months ago
Exploiting efficient data mining techniques to enhance intrusion detection systems
- Security is becoming a critical part of organizational information systems. Intrusion Detection System (IDS) is an important detection that is used as a countermeasure to preserv...
Chang-Tien Lu, Arnold P. Boedihardjo, Prajwal Mana...
ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
14 years 1 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...