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ESANN
2006
13 years 9 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...
GECCO
2003
Springer
130views Optimization» more  GECCO 2003»
14 years 25 days ago
A New Approach to Improve Particle Swarm Optimization
Abstract. Particle swarm optimization (PSO) is a new evolutionary computation technique. Although PSO algorithm possesses many attractive properties, the methods of selecting inert...
Liping Zhang, Huanjun Yu, Shangxu Hu
CEC
2008
IEEE
14 years 2 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...
CVPR
2010
IEEE
14 years 3 months ago
Parametric Dimensionality Reduction by Unsupervised Regression
We introduce a parametric version (pDRUR) of the recently proposed Dimensionality Reduction by Unsupervised Regression algorithm. pDRUR alternately minimizes reconstruction error ...
Miguel Carreira-perpinan, Zhengdong Lu
NIPS
2007
13 years 9 months ago
Feature Selection Methods for Improving Protein Structure Prediction with Rosetta
Rosetta is one of the leading algorithms for protein structure prediction today. It is a Monte Carlo energy minimization method requiring many random restarts to find structures ...
Ben Blum, Michael I. Jordan, David Kim, Rhiju Das,...