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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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ML
2010
ACM
135views Machine Learning» more  ML 2010»
14 years 4 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
14 years 11 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
INFOVIS
2000
IEEE
15 years 2 months ago
Interactive Problem Solving via Algorithm Visualization
COMIND is a tool for conceptual design of industrial products. It helps designers define and evaluate the initial design space by using search algorithms to generate sets of feasi...
Pearl Pu, Denis Lalanne
BMCBI
2006
99views more  BMCBI 2006»
14 years 10 months ago
Genetic algorithm learning as a robust approach to RNA editing site prediction
Background: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One f...
James Thompson, Shuba Gopal
SIGIR
2010
ACM
15 years 1 months ago
Extending average precision to graded relevance judgments
Evaluation metrics play a critical role both in the context of comparative evaluation of the performance of retrieval systems and in the context of learning-to-rank (LTR) as objec...
Stephen E. Robertson, Evangelos Kanoulas, Emine Yi...