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BMCBI
2004
252views more  BMCBI 2004»
13 years 10 months ago
Applying Support Vector Machines for Gene ontology based gene function prediction
Background: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to ann...
Arunachalam Vinayagam, Rainer König, Jutta Mo...
DCC
2006
IEEE
14 years 10 months ago
Non-Asymptotic Design of Finite State Universal Predictors for Individual Sequences
In this work we consider the problem of universal prediction of individual sequences where the universal predictor is a deterministic finite state machine, with a fixed, relativel...
Amir Ingber, Meir Feder
FLAIRS
2007
14 years 1 months ago
Naive Bayes and Decision Trees for Function Tagging
This paper describes the use of two machine learning techniques, naive Bayes and decision trees, to address the task of assigning function tags to nodes in a syntactic parse tree....
Mihai C. Lintean, Vasile Rus
CIKM
2009
Springer
14 years 2 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
GPEM
2008
128views more  GPEM 2008»
13 years 11 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood