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(RF)^2 - Random Forest Random Field
2010
Neural Information Processing Systems
We combine random forest (RF) and conditional random field (CRF) into a new computational framework, called random forest random field (RF) 2 . Inference of (RF) 2 uses the Swendsen-Wang cut algorithm, characterized by Metropolis-Hastings jumps. A jump from one state to another depends on the ratio of the proposal distributions, and on the ratio of the posterior distributions of the two states. Prior work typically resorts to a parametric estimation of these four distributions, and then
dblp:conf/nips/PayetT10
fatcat:lcaurkzvufeh7keoocv4v4tamm