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JMLR
2010
118views more  JMLR 2010»
14 years 5 months ago
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Gavin C. Cawley, Nicola L. C. Talbot
101
Voted
BMCBI
2011
14 years 1 months ago
Biomarker Discovery and Redundancy Reduction towards Classification using a Multi-factorial MALDI-TOF MS T2DM Mouse Model Datase
Background: Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its c...
Chris Bauer, Frank Kleinjung, Celia J. Smith, Mark...
SIGIR
2011
ACM
14 years 1 months ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen
127
Voted
CORR
2012
Springer
204views Education» more  CORR 2012»
13 years 6 months ago
Ontologies for the Integration of Air Quality Models and 3D City Models
In the perspective of a sustainable urban planning, it is necessary to investigate cities in a holistic way and to accept surprises in the response of urban environments to a part...
Claudine Métral, Gilles Falquet, Kostas Kar...
128
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JMLR
2012
13 years 21 days ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
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