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ICANN
2011
Springer
14 years 3 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»
14 years 11 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
15 years 1 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»
14 years 11 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