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ALT
2010
Springer
15 years 4 months ago
Contrast Pattern Mining and Its Application for Building Robust Classifiers
: The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their d...
Kotagiri Ramamohanarao
VLSISP
2010
254views more  VLSISP 2010»
15 years 1 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
127
Voted
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 1 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
CEAS
2007
Springer
15 years 7 months ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
138
Voted
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
15 years 1 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