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Acknowledgements This study was partially supported by the FP7 project "CAse studies on the development and application of in-silica techniques for environmental hazard and risk assessment" ( ... The observance that PLS-Optimal has a lower variability in selection than DescRep is coherent as the D-Optimal criterion also has lower variability than MDC. ... The latent variables in our implementation are derived from a PLS model on the pre-selected compounds. ...doi:10.5936/csbj.201305002 pmid:24688738 pmcid:PMC3962228 fatcat:idtfxyq74zfsth5mmi2g5gc6cm
Kernel boosted latent features (KBLF) is a variant of KPLS for any differentiable loss functions. ... The algorithm provides an interesting "path" from a maximum residual criterion based algorithm with orthogonality conditions to the dense KPLS/KBLF. ... or another way of optimizing the coefficient based on the loss function. ...doi:10.1145/1081870.1081952 dblp:conf/kdd/Momma05 fatcat:colpqr62bvd7tntekj3lm3z2hq