GECCO
2008
Springer
14 years 27 days ago
2008
Springer
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 ...
GECCO
2008
Springer
14 years 27 days ago
2008
Springer
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 ...
CLEF
2010
Springer
14 years 28 days ago
2010
Springer
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...
CLEF
2010
Springer
14 years 28 days ago
2010
Springer
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...
COLING
2000
14 years 1 months ago
2000
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...
PICS
2003
14 years 1 months ago
2003
To establish a correlation between the system output and the corresponding reflectance, the system characterisation functionDeriving the actual multispectral data from the output o...
NIPS
2004
14 years 1 months ago
2004
We propose to selectively remove examples from the training set using probabilistic estimates related to editing algorithms (Devijver and Kittler, 1982). This heuristic procedure ...
NCI
2004
14 years 1 months ago
2004
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...
LWA
2004
14 years 1 months ago
2004
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...
FLAIRS
2006
14 years 1 months ago
2006
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...