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ICML
2010
IEEE
15 years 7 months ago
Unsupervised Risk Stratification in Clinical Datasets: Identifying Patients at Risk of Rare Outcomes
Most existing algorithms for clinical risk stratification rely on labeled training data. Collecting this data is challenging for clinical conditions where only a small percentage ...
Zeeshan Syed, Ilan Rubinfeld
MLDM
2008
Springer
15 years 6 months ago
Classification Based on Consistent Itemset Rules
Abstract. We propose an approach to build a classifier composing consistent (100% confident) rules. Recently, associative classifiers that utilize association rules have been widel...
Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura
ML
2010
ACM
193views Machine Learning» more  ML 2010»
15 years 1 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
ICML
2003
IEEE
16 years 7 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 7 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...