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» Training of Classifiers Using Virtual Samples Only
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JMLR
2010
136views more  JMLR 2010»
13 years 3 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
PR
2006
111views more  PR 2006»
13 years 9 months ago
An adaptive error penalization method for training an efficient and generalized SVM
A novel training method has been proposed for increasing efficiency and generalization of support vector machine (SVM). The efficiency of SVM in classification is directly determi...
Yiqiang Zhan, Dinggang Shen
IJON
2006
95views more  IJON 2006»
13 years 9 months ago
Ensemble classifiers based on correlation analysis for DNA microarray classification
Since accurate classification of DNA microarray is a very important issue for the treatment of cancer, it is more desirable to make a decision by combining the results of various ...
Kyung-Joong Kim, Sung-Bae Cho
ICPR
2008
IEEE
14 years 3 months ago
Grading nuclear pleomorphism on histological micrographs
A mainstay in cancer diagnostics is the classification or grading of cell nuclei based on their appearance. While the analysis of cytological samples has been automated successful...
Eric Cosatto, Matthew Miller, Hans Peter Graf, Joh...
CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
14 years 24 days ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong