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» Applying Support Vector Machines to Imbalanced Datasets
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NN
2007
Springer
106views Neural Networks» more  NN 2007»
13 years 8 months ago
Machine learning approach to color constancy
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Vivek Agarwal, Andrei V. Gribok, Mongi A. Abidi
BMCBI
2007
173views more  BMCBI 2007»
13 years 9 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
ESANN
2006
13 years 10 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
ACII
2011
Springer
12 years 9 months ago
Investigating the Prosody and Voice Quality of Social Signals in Scenario Meetings
Abstract. In this study we propose a methodology to investigate possible prosody and voice quality correlates of social signals, and test-run it on annotated naturalistic recording...
Marcela Charfuelan, Marc Schröder
FGR
2011
IEEE
201views Biometrics» more  FGR 2011»
13 years 15 days ago
Tangent bundle for human action recognition
— Common human actions are instantly recognizable by people and increasingly machines need to understand this language if they are to engage smoothly with people. Here we introdu...
Yui Man Lui, J. Ross Beveridge