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MCS
2007
Springer
14 years 3 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
ECML
2006
Springer
14 years 22 days ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...
LREC
2010
176views Education» more  LREC 2010»
13 years 10 months ago
There's no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
In the paper we investigate the impact of data size on a Word Sense Disambiguation task (WSD). We question the assumption that the knowledge acquisition bottleneck, which is known...
Ines Rehbein, Josef Ruppenhofer
DIS
2008
Springer
13 years 10 months ago
Unsupervised Classifier Selection Based on Two-Sample Test
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a s...
Timo Aho, Tapio Elomaa, Jussi Kujala
ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 9 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...