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» Evaluating learning algorithms and classifiers
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BMCBI
2008
114views more  BMCBI 2008»
15 years 4 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
AAAI
1997
15 years 5 months ago
Symbolic Nearest Mean Classifiers
The minimum-distance classifier summarizes each class with a prototype and then uses a nearest neighbor approach for classification. Three drawbacks of the original minimum-distan...
Piew Datta, Dennis F. Kibler
SIGIR
2002
ACM
15 years 3 months ago
Bayesian online classifiers for text classification and filtering
This paper explores the use of Bayesian online classifiers to classify text documents. Empirical results indicate that these classifiers are comparable with the best text classifi...
Kian Ming Adam Chai, Hai Leong Chieu, Hwee Tou Ng
ML
2006
ACM
109views Machine Learning» more  ML 2006»
15 years 4 months ago
Cost curves: An improved method for visualizing classifier performance
Abstract This paper introduces cost curves, a graphical technique for visualizing the performance (error rate or expected cost) of 2-class classifiers over the full range of possib...
Chris Drummond, Robert C. Holte
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
15 years 5 months ago
Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins
A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
Greg Paperin