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ESANN
2006
15 years 5 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...
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
16 years 4 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
ISCI
2008
165views more  ISCI 2008»
15 years 4 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
IJDMB
2007
110views more  IJDMB 2007»
15 years 4 months ago
Transductive learning with EM algorithm to classify proteins based on phylogenetic profiles
: Phylogenetic profiles of proteins  strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes  have recently been used to id...
Roger A. Craig, Li Liao
CVPR
2009
IEEE
16 years 11 months ago
Echocardiogram View Classification using Edge Filtered Scale-invariant Motion Features
In an 2D echocardiogram exam, an ultrasound probe samples the heart with 2D slices. Changing the orientation and position on the probe changes the slice viewpoint, altering the ...
Ritwik Kumar, Fei Wang, David Beymer, Tanveer Fath...