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147
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JMLR
2010
102views more  JMLR 2010»
14 years 10 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
140
Voted
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
15 years 8 months ago
A genetic algorithm for learning significant phrase patterns in radiology reports
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. R...
Robert M. Patton, Thomas E. Potok, Barbara G. Beck...
138
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DAGM
2006
Springer
15 years 7 months ago
Handling Camera Movement Constraints in Reinforcement Learning Based Active Object Recognition
In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
Christian Derichs, Heinrich Niemann
135
Voted
ICML
2010
IEEE
15 years 3 months ago
Application of Machine Learning To Epileptic Seizure Detection
We present and evaluate a machine learning approach to constructing patient-specific classifiers that detect the onset of an epileptic seizure through analysis of the scalp EEG, a...
Ali H. Shoeb, John V. Guttag
154
Voted
TNN
2008
105views more  TNN 2008»
15 years 3 months ago
Incremental Learning of Chunk Data for Online Pattern Classification Systems
This paper presents a pattern classification system in which feature extraction and classifier learning are simultaneously carried out not only online but also in one pass where tr...
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov