Package: fscaret 0.9.4.4

fscaret: Automated Feature Selection from 'caret'

Automated feature selection using variety of models provided by 'caret' package. This work was funded by Poland-Singapore bilateral cooperation project no 2/3/POL-SIN/2012.

Authors:Jakub Szlek [aut, cre], Aleksander Mendyk [ctb]

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fscaret.pdf |fscaret.html✨
fscaret/json (API)
NEWS

# Install 'fscaret' in R:

install.packages('fscaret', repos = c('https://jszlek.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jszlek/fscaret/issues

Datasets:

dataset.test - Example testing data set
dataset.train - Example training data set
funcClassPred - Classification methods used.
funcRegPred - All regression methods used
requiredPackages - RequiredPackages

On CRAN:

3.97 score 31 scripts 324 downloads 3 mentions 13 exports 78 dependencies

Last updated 7 years agofrom:1c56431c2f. Checks:OK: 3 NOTE: 4. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 10 2024
R-4.5-win	OK	Nov 10 2024
R-4.5-linux	OK	Nov 10 2024
R-4.4-win	NOTE	Nov 10 2024
R-4.4-mac	NOTE	Nov 10 2024
R-4.3-win	NOTE	Nov 10 2024
R-4.3-mac	NOTE	Nov 10 2024

Exports:classVarImp dataPreprocess fscaret funcClassPred funcRegPred impCalc impute.mean installPckg MSE regVarImp requiredPackages RMSE timeout

Dependencies:caret class cli clock codetools colorspace cpp11 data.table diagram digest dplyr e1071 fansi farver foreach future future.apply generics ggplot2 globals glue gower gsubfn gtable hardhat hmeasure ipred isoband iterators KernSmooth labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix mgcv ModelMetrics munsell nlme nnet numDeriv parallelly pillar pkgconfig plyr pROC prodlim progressr proto proxy purrr R6 RColorBrewer Rcpp recipes reshape2 rlang rpart scales shape SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr

A short fscaret package introduction with examples

Rendered fromfscaret.Rnwusingutils::Sweaveon Nov 10 2024.

Last update: 2017-12-12
Started: 2013-06-28

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Automated feature selection caret (fscaret)	fscaret-package
classVarImp	classVarImp
dataPreprocess	dataPreprocess
Example testing data set	dataset.test
Example training data set	dataset.train
feature selection caret	fscaret
Classification methods used.	funcClassPred
All regression methods used	funcRegPred
impCalc	impCalc
imputeMean	impute.mean
installPckg	installPckg
MSE	MSE
regVarImp	regVarImp
requiredPackages	requiredPackages
RMSE	RMSE
timeout	timeout