[package]mboost

《[package]mboost 》由会员上传分享，免费在线阅读，更多相关内容在学术论文-天天文库。

1、Package‘mboost’February29,2012TitleModel-BasedBoostingVersion2.1-2Date2012-02-29DescriptionFunctionalgradientdescentalgorithm(boosting)foroptimizinggeneralriskfunctionsutilizingcomponent-wise(penalised)leastsquaresestimatesorregressiontreesasbase-learnersforfittinggeneralizedlinear,additiveandintera

2、ctionmodelstopotentiallyhigh-dimensionaldata.DependsR(>=2.10.0),methods,statsImportsMatrix,survival,splines,latticeSuggestsmulticore,party(>=0.9-9993),ipred,MASS,fields,BayesX,gbm,mlbench,RColorBrewerLazyLoadyesLazyDatayesLicenseGPL-2AuthorTorstenHothorn[aut,cre],PeterBuehlmann[aut],ThomasKneib[aut]

3、,MatthiasSchmid[aut],BenjaminHofner[aut]MaintainerTorstenHothornRepositoryCRANDate/Publication2012-02-2914:32:46Rtopicsdocumented:mboost-package.......................................2baselearners.........................................4birds.........................

4、....................15blackboost..........................................16bodyfat...........................................1812mboost-packageboost_control........................................20boost_family-class.....................................21cvrisk.....................................

5、.......22Family............................................25FP..............................................29gamboost..........................................30glmboost..........................................32IPCweights.........................................35mboost.........................

6、...................36methods...........................................38stabsel............................................45survFit............................................46Westbc............................................48wpbc.............................................49Index51mboost-pac

7、kagemboost:Model-BasedBoostingDescriptionFunctionalgradientdescentalgorithm(boosting)foroptimizinggeneralriskfunctionsutilizingcomponent-wise(penalised)leastsquaresestimatesorregressiontreesasbase-learnersf