Methodology: Remove one observation. Training the rest of data that are sampled without replacement and given this observation's input, predict the response back. Replicate this N times and for each response, take a sample from these replicates with replacement. Average each responses of sample and again replicate this step N time for each observation. Approximate these N new responses by using bootstrap method and generate another N responses y'. Training these y' and predict to have N responses of each testing observation. The average of N is the final prediction. Each observation will do the same.
Version: | 0.4 |
Depends: | R (≥ 3.2.5), rpart , parallel, caret, nnet, pls |
Suggests: | MASS |
Published: | 2018-07-07 |
Author: | Moshu Xie |
Maintainer: | Moshu Xie <mxie622 at gmail.com> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | SQB results |
Reference manual: | SQB.pdf |
Package source: | SQB_0.4.tar.gz |
Windows binaries: | r-devel: SQB_0.4.zip, r-release: SQB_0.4.zip, r-oldrel: SQB_0.4.zip |
macOS binaries: | r-release: SQB_0.4.tgz, r-oldrel: SQB_0.4.tgz |
Old sources: | SQB archive |
Please use the canonical form https://CRAN.R-project.org/package=SQB to link to this page.