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» Evaluating learning algorithms and classifiers
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ICST
2009
IEEE
15 years 10 months ago
A Model Building Process for Identifying Actionable Static Analysis Alerts
Automated static analysis can identify potential source code anomalies early in the software process that could lead to field failures. However, only a small portion of static ana...
Sarah Smith Heckman, Laurie A. Williams
CVPR
2008
IEEE
16 years 6 months ago
Multiple-instance ranking: Learning to rank images for image retrieval
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
Yang Hu, Mingjing Li, Nenghai Yu
JMLR
2006
134views more  JMLR 2006»
15 years 3 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz
ICCV
2003
IEEE
16 years 5 months ago
Learning a Classification Model for Segmentation
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly m...
Xiaofeng Ren, Jitendra Malik
IDA
2006
Springer
15 years 4 months ago
Classification of symbolic objects: A lazy learning approach
Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
Annalisa Appice, Claudia d'Amato, Floriana Esposit...