SuperLearner: Super Learner Prediction
Implements the super learner prediction method and contains a
library of prediction algorithms to be used in the super learner.
Version:
2.0-29
Depends:
R (≥ 2.14.0),
nnls,
gam (≥ 1.15)
Suggests:
arm,
bartMachine,
biglasso,
bigmemory,
caret,
class,
devtools,
e1071,
earth,
gbm,
genefilter,
ggplot2,
glmnet,
ipred,
KernelKnn,
kernlab,
knitr,
lattice,
LogicReg,
MASS,
mlbench,
nloptr,
nnet,
party,
polspline,
prettydoc,
quadprog,
randomForest,
ranger,
RhpcBLASctl,
ROCR,
rmarkdown,
rpart,
SIS,
speedglm,
spls,
sva,
testthat,
xgboost (≥ 0.6)
Published:
2024年02月20日
Author:
Eric Polley [aut, cre],
Erin LeDell [aut],
Chris Kennedy [aut],
Sam Lendle [ctb],
Mark van der Laan [aut, ths]
Maintainer:
Eric Polley <epolley at uchicago.edu>
NeedsCompilation:
no
Documentation:
Downloads:
Reverse dependencies:
Reverse imports:
AIPW,
amp,
CausalGPS,
CausalMetaR,
causalweight,
CIMTx,
CompMix,
CRE,
crossurr,
DeepLearningCausal,
DRDRtest,
drpop,
drtmle,
evalITR,
flevr,
GPCERF,
lmtp,
nlpred,
PND.heter.cluster,
PSweight,
Ricrt,
RISCA,
RobinCar,
tehtuner,
tidyhte,
vaccine,
vimp
Reverse suggests:
biotmle,
gKRLS,
hal9001,
ltmle,
medflex,
MRTAnalysis,
nestedcv,
riskRegression,
targeted,
vglmer,
WeightIt
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