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» Learning to Classify Texts Using Positive and Unlabeled Data
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MICAI
2007
Springer
14 years 1 months ago
Taking Advantage of the Web for Text Classification with Imbalanced Classes
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...
CVPR
2004
IEEE
14 years 9 months ago
Improving Object Classification in Far-Field Video
Object classification in far-field video sequences is a challenging problem because of low resolution imagery and projective image distortion. Most existing far-field classificati...
Biswajit Bose, W. Eric L. Grimson
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
13 years 11 months ago
Sets of receiver operating characteristic curves and their use in the evaluation of multi-class classification
Within the last two decades, Receiver Operating Characteristic (ROC) Curves have become a standard tool for the analysis and comparison of classifiers since they provide a conveni...
Stephan M. Winkler, Michael Affenzeller, Stefan Wa...
CORR
2002
Springer
96views Education» more  CORR 2002»
13 years 7 months ago
Thumbs up? Sentiment Classification using Machine Learning Techniques
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, w...
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan
ECCV
2008
Springer
14 years 9 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert