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ICANN
2011
Springer
12 years 11 months ago
Bias of Importance Measures for Multi-valued Attributes and Solutions
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
Houtao Deng, George C. Runger, Eugene Tuv
ETT
2002
77views Education» more  ETT 2002»
13 years 7 months ago
On the importance function in splitting simulation
The splitting method is a simulation technique for the estimation of very small probabilities. In this technique, the sample paths are split into multiple copies, at various stages...
Marnix J. J. Garvels, Jan-Kees C. W. van Ommeren, ...
EMNLP
2004
13 years 9 months ago
Unsupervised WSD based on Automatically Retrieved Examples: The Importance of Bias
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
Eneko Agirre, David Martínez
BMCBI
2005
121views more  BMCBI 2005»
13 years 7 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu