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» A Case Study for Learning from Imbalanced Data Sets
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CVPR
2011
IEEE
14 years 10 months ago
Multi-label Learning with Incomplete Class Assignments
We consider a special type of multi-label learning where class assignments of training examples are incomplete. As an example, an instance whose true class assignment is (c1, c2, ...
Serhat Bucak, Rong Jin, Anil Jain
ICML
2001
IEEE
16 years 7 months ago
Constrained K-means Clustering with Background Knowledge
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...
WWW
2004
ACM
16 years 6 months ago
Online feedback by tests and reporting for elearning and certification programs
The evaluation of eLearning success is an indispensable business requirement of education programs: the easy registration of `visits' to eLearning websites is, however, not s...
Dirk Bade, Georg Nüssel, Gerd Wilts
ICML
2009
IEEE
16 years 7 months ago
Robust feature extraction via information theoretic learning
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
Xiaotong Yuan, Bao-Gang Hu
ICDM
2005
IEEE
117views Data Mining» more  ICDM 2005»
15 years 11 months ago
On Learning Asymmetric Dissimilarity Measures
Many practical applications require that distance measures to be asymmetric and context-sensitive. We introduce Context-sensitive Learnable Asymmetric Dissimilarity (CLAD) measure...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...