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ICAISC
2010
Springer
13 years 9 months ago
Pruning Classification Rules with Reference Vector Selection Methods
Attempts to extract logical rules from data often lead to large sets of classification rules that need to be pruned. Training two classifiers, the C4.5 decision tree and the Non-Ne...
Karol Grudzinski, Marek Grochowski, Wlodzislaw Duc...
APIN
2008
110views more  APIN 2008»
13 years 9 months ago
Explaining inferences in Bayesian networks
While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall sh...
Ghim-Eng Yap, Ah-Hwee Tan, HweeHwa Pang
BMCBI
2010
114views more  BMCBI 2010»
13 years 9 months ago
Detection of gene orthology from gene co-expression and protein interaction networks
Background: Ortholog detection methods present a powerful approach for finding genes that participate in similar biological processes across different organisms, extending our und...
Fadi Towfic, Susan VanderPlas, Casey A. Oliver, Ol...
CONSTRAINTS
2010
101views more  CONSTRAINTS 2010»
13 years 9 months ago
Constraint models for graceful graphs
Abstract. We present three constraint models of the problem of finding a graceful labelling of a graph, or proving that the graph is not graceful. An experimental comparison of the...
Barbara M. Smith, Jean-François Puget
ACTAC
2006
126views more  ACTAC 2006»
13 years 8 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...