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GECCO
2008
Springer
184views Optimization» more  GECCO 2008»
9 years 1 months ago
Analysis of mammography reports using maximum variation sampling
A genetic algorithm (GA) was developed to implement a maximum variation sampling technique to derive a subset of data from a large dataset of unstructured mammography reports. It ...
Robert M. Patton, Barbara G. Beckerman, Thomas E. ...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
9 years 1 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
CLEF
2010
Springer
9 years 1 months ago
ZOT! to Wikipedia Vandalism - Lab Report for PAN at CLEF 2010
Abstract This vandalism detector uses features primarily derived from a wordpreserving differencing of the text for each Wikipedia article from before and after the edit, along wit...
James White, Rebecca Maessen
CLEF
2010
Springer
9 years 1 months ago
The Wroclaw University of Technology Participation at ImageCLEF 2010 Photo Annotation Track
Abstract. In this paper we present three methods for image autoannotation used by the Wroclaw University of Technology group at ImageCLEF 2010 Photo Annotation track. All of our ex...
Michal Stanek, Oskar Maier, Halina Kwasnicka
COLING
2000
9 years 1 months ago
Estimation of Stochastic Attribute-Value Grammars using an Informative Sample
We argue that some of the computational complexity associated with estimation of stochastic attributevalue grammars can be reduced by training upon an informative subset of the fu...
Miles Osborne
PICS
2003
9 years 1 months ago
Selection of Training Sets for the Characterisation of Multispectral Imaging Systems
To establish a correlation between the system output and the corresponding reflectance, the system characterisation functionDeriving the actual multispectral data from the output o...
Paolo Pellegri, Gianluca Novati, Raimondo Schettin...
NIPS
2004
9 years 1 months ago
Breaking SVM Complexity with Cross-Training
We propose to selectively remove examples from the training set using probabilistic estimates related to editing algorithms (Devijver and Kittler, 1982). This heuristic procedure ...
Gökhan H. Bakir, Léon Bottou, Jason We...
NCI
2004
188views Neural Networks» more  NCI 2004»
9 years 1 months ago
Training set optimization in 3D human face recognition by RBF neural networks
In the Neural Networks approach by Radial Basis Function - RBF, the property of interpolation between faces, their variation, and the diversity of faces helps to minimize the outp...
Antonio C. Zimmermann, L. S. Encinas, L. O. Marin,...
LWA
2004
9 years 1 months ago
Modeling Rule Precision
This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
Johannes Fürnkranz
FLAIRS
2006
9 years 1 months ago
Using Validation Sets to Avoid Overfitting in AdaBoost
AdaBoost is a well known, effective technique for increasing the accuracy of learning algorithms. However, it has the potential to overfit the training set because its objective i...
Tom Bylander, Lisa Tate
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