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CVIU
2006
160views more  CVIU 2006»
15 years 6 months ago
Automatic selection of edge detector parameters based on spatial and statistical measures
The basic and widely used edge detection operation in an image usually requires a prior step of setting the edge detector parameters (thresholds, blurring extent etc.). Finding th...
Raz Koren, Yitzhak Yitzhaky
ESWA
2006
154views more  ESWA 2006»
15 years 6 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim
JMM2
2008
124views more  JMM2 2008»
15 years 6 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang
JMLR
2006
99views more  JMLR 2006»
15 years 6 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
EOR
2007
85views more  EOR 2007»
15 years 6 months ago
Reject inference, augmentation, and sample selection
Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Al...
John Banasik, Jonathan Crook