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» Generality Is Predictive of Prediction Accuracy
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KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 7 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
178
Voted
MLDM
2007
Springer
16 years 25 days ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
201
Voted
GECCO
2010
Springer
186views Optimization» more  GECCO 2010»
15 years 7 months ago
Genetic rule extraction optimizing brier score
Most highly accurate predictive modeling techniques produce opaque models. When comprehensible models are required, rule extraction is sometimes used to generate a transparent mod...
Ulf Johansson, Rikard König, Lars Niklasson
BMCBI
2008
96views more  BMCBI 2008»
15 years 6 months ago
The value of position-specific scoring matrices for assessment of protein allegenicity
Background: Bioinformatics tools are commonly used for assessing potential protein allergenicity. While these methods have achieved good accuracies for highly conserved sequences,...
Shen Jean Lim, Joo Chuan Tong, Fook Tim Chew, Mart...
FGCS
2006
74views more  FGCS 2006»
15 years 6 months ago
A performance model of non-deterministic particle transport on large-scale systems
In this work we present a predictive analytical model that encompasses the performance and scaling characteristics of a nondeterministic particle transport application, MCNP (Mont...
Mark M. Mathis, Darren J. Kerbyson, Adolfy Hoisie