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» Learning Rules from Distributed Data
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ICCV
2003
IEEE
16 years 4 months ago
Machine Learning and Multiscale Methods in the Identification of Bivalve Larvae
This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
Sanjay Tiwari, Scott Gallager
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
15 years 4 months ago
Roughly Balanced Bagging for Imbalanced Data
Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
Shohei Hido, Hisashi Kashima
IPSN
2010
Springer
15 years 9 months ago
Online distributed sensor selection
A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to co...
Daniel Golovin, Matthew Faulkner, Andreas Krause
TNN
2010
127views Management» more  TNN 2010»
14 years 9 months ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia
ISORC
2000
IEEE
15 years 7 months ago
Establishing a Data-Mining Environment for Wartime Event Prediction with an Object-Oriented Command and Control Database
This paper documents progress to date on a research project, the goal of which is wartime event prediction. The paper describes the operational concept, the datamining environment...
Marion G. Ceruti, S. Joe McCarthy