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» Training Data Selection for Support Vector Machines
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160
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ICML
1998
IEEE
16 years 6 months ago
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
Paul S. Bradley, Olvi L. Mangasarian
163
Voted
ICASSP
2010
IEEE
15 years 6 months ago
Training a support vector machine to classify signals in a real environment given clean training data
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...
194
Voted
IJCNN
2006
IEEE
15 years 12 months ago
Classify Unexpected News Impacts to Stock Price by Incorporating Time Series Analysis into Support Vector Machine
— the paper discusses an approach of using traditional time series analysis, as domain knowledge, to help the data-preparation of support vector machine for classifying documents...
Ting Yu, Tony Jan, John K. Debenham, Simeon J. Sim...
164
Voted
ICCS
2007
Springer
15 years 12 months ago
Active Learning with Support Vector Machines for Tornado Prediction
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...
146
Voted
ICPR
2008
IEEE
16 years 7 days ago
Fast model selection for MaxMinOver-based training of support vector machines
OneClassMaxMinOver (OMMO) is a simple incremental algorithm for one-class support vector classification. We propose several enhancements and heuristics for improving model select...
Fabian Timm, Sascha Klement, Thomas Martinetz